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Master of BusinessAdministration – MBA Semester 3 

Name:Meenakshi

 Roll No.:

520967713 

Subject:Marketing Management 

Subject

code: MB0034

ResearchMethodology

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  ASSIGNMENT SET-1

Q 1. Give examples of specific situations that would call for the following types of research, explaining why – a) Exploratory research b) Descriptive research c) Diagnosticresearch d) Evaluation research.

Ans.: Research may be classified crudely according to its major intent or the methods. According

to the intent, research may be classified as:Basic (aka fundamental or pure) research is driven by a scientist's curiosity or interest in ascientific question. The main motivation is to expand man's knowledge, not to create or inventsomething. There is no obvious commercial value to the discoveries that result from basicresearch.

For example, basic science investigations probe for answers to questions such as:• How did the universe begin?

• What are protons, neutrons, and electrons composed of?

• How do slime molds reproduce?

• What is the specific genetic code of the fruit fly?

Most scientists believe that a basic, fundamental understanding of all branches of science isneeded in order for progress to take place. In other words, basic research lays down thefoundation for the applied science that follows. If basic work is done first, then applied spin-offsoften eventually result from this research. As Dr. George Smoot of LBNL says, "People cannotforesee the future well enough to predict what's going to develop from basic research. If we onlydid applied research, we would still be making better spears."

Applied research is designed to solve practical problems of the modern world, rather than toacquire knowledge for knowledge's sake. One might say that the goal of the applied scientist is toimprove the human condition.

For example, applied researchers may investigate ways to:• Improve agricultural crop production

• Treat or cure a specific disease

• Improve the energy efficiency of homes, offices, or modes of transportation

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Some scientists feel that the time has come for a shift in emphasis away from purely basicresearch and toward applied science. This trend, they feel, is necessitated by the problemsresulting from global overpopulation, pollution, and the overuse of the earth's natural resources.Exploratory research provides insights into and comprehension of an issue or situation. Itshould draw definitive conclusions only with extreme caution. Exploratory research is a type of research conducted because a problem has not been clearly defined. Exploratory research helpsdetermine the best research design, data collection method and selection of subjects. Given itsfundamental nature, exploratory research often concludes that a perceived problem does notactually exist.Exploratory research often relies on secondary research such as reviewing available literatureand/or data, or qualitative approaches such as informal discussions with consumers, employees,management or competitors, and more formal approaches through in-depth interviews, focusgroups, projective methods, case studies or pilot studies. The Internet allows for researchmethods that are more interactive in nature: E.g., RSS feeds efficiently supply researchers withup-to-date information; major search engine search results may be sent by email to researchersby services such as Google Alerts; comprehensive search results are tracked over lengthyperiods of time by services such as Google Trends; and Web sites may be created to attractworldwide feedback on any subject.The results of exploratory research are not usually useful for decision-making by themselves, butthey can provide significant insight into a given situation. Although the results of qualitative

research can give some indication as to the "why", "how" and "when" something occurs, it cannottell us "how often" or "how many."Exploratory research is not typically generalizable to the population at large.A defining characteristic of causal research is the random assignment of participants to theconditions of the experiment; e.g., an Experimental and a Control Condition... Such assignmentresults in the groups being comparable at the beginning of the experiment. Any differencebetween the groups at the end of the experiment is attributable to the manipulated variable.Observational research typically looks for difference among "in-tact" defined groups. A commonexample compares smokers and non-smokers with regard to health problems. Causalconclusions can't be drawn from such a study because of other possible differences between thegroups; e.g., smokers may drink more alcohol than non-smokers. Other unknown differencescould exist as well. Hence, we may see a relation between smoking and health but a conclusionthat smoking is a cause would not be warranted in this situation. (Cp)

Descriptive research, also known as statistical research, describes data and characteristicsabout the population or phenomenon being studied. Descriptive research answers the questionswho, what, where, when and how.Although the data description is factual, accurate and systematic, the research cannot describewhat caused a situation. Thus, descriptive research cannot be used to create a causalrelationship, where one variable affects another. In other words, descriptive research can be saidto have a low requirement for internal validity.The description is used for frequencies, averages and other statistical calculations. Often the bestapproach, prior to writing descriptive research, is to conduct a survey investigation. Qualitativeresearch often has the aim of description and researchers may follow-up with examinations of why the observations exist and what the implications of the findings are.In short descriptive research deals with everything that can be counted and studied. But there arealways restrictions to that. Your research must have an impact to the life of the people around

you. For example, finding the most frequent disease that affects the children of a town. Thereader of the research will know what to do to prevent that disease thus; more people will live ahealthy life.Diagnostic study : it is similar to descriptive study but with different focus. It is directed towardsdiscovering what is happening and what can be done about. It aims at identifying the causes of aproblem and the possible solutions for it. It may also be concerned with discovering and testingwhether certain variables are associated. This type of research requires prior knowledge of theproblem, its thorough formulation, clear-cut definition of the given population, adequate methodsfor collecting accurate information, precise measurement of variables, statistical analysis and testof significance.

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Evaluation Studies: it is a type of applied research. It is made for assessing the effectiveness of social or economic programmes implemented or for assessing the impact of development of theproject area. It is thus directed to assess or appraise the quality and quantity of an activity and itsperformance and to specify its attributes and conditions required for its success. It is concernedwith causal relationships and is more actively guided by hypothesis. It is concerned also withchange over time.Action research is a reflective process of progressive problem solving led by individuals workingwith others in teams or as part of a "community of practice" to improve the way they addressissues and solve problems. Action research can also be undertaken by larger organizations or institutions, assisted or guided by professional researchers, with the aim of improving their strategies, practices, and knowledge of the environments within which they practice. As designersand stakeholders, researchers work with others to propose a new course of action to help their community improve its work practices (Center for Collaborative Action Research). Kurt Lewin,then a professor at MIT, first coined the term “action research” in about 1944, and it appears inhis 1946 paper “Action Research and Minority Problems”. In that paper, he described actionresearch as “a comparative research on the conditions and effects of various forms of socialaction and research leading to social action” that uses “a spiral of steps, each of which iscomposed of a circle of planning, action, and fact-finding about the result of the action”.Action research is an interactive inquiry process that balances problem solving actionsimplemented in a collaborative context with data-driven collaborative analysis or research to

understand underlying causes enabling future predictions about personal and organizationalchange (Reason & Bradbury, 2001). After six decades of action research development, manymethodologies have evolved that adjust the balance to focus more on the actions taken or moreon the research that results from the reflective understanding of the actions. This tension existsbetween

● those that are more driven by the researcher’s agenda to those more driven by

participants;

• Those that are motivated primarily by instrumental goal attainment to those motivatedprimarily by the aim of personal, organizational, or societal transformation; and

• 1st-, to 2nd-, to 3rd-person research, that is, my research on my own action, aimedprimarily at personal change; our research on our group (family/team), aimedprimarily at improving the group; and ‘scholarly’ research aimed primarily attheoretical generalization and/or large scale change.

Action research challenges traditional social science, by moving beyond reflective knowledgecreated by outside experts sampling variables to an active moment-to-moment theorizing, datacollecting, and inquiring occurring in the midst of emergent structure. “Knowledge is alwaysgained through action and for action. From this starting point, to question the validity of socialknowledge is to question, not how to develop a reflective science about action, but how todevelop genuinely well-informed action how to conduct an action science” (Tolbert 2001).

Q 2.In the context of hypothesis testing, briefly explain the difference between a) Null andalternative hypothesis b) Type 1 and type 2 error c) Two tailed and one tailed test d)

Parametric and non-parametric tests.

Ans.: Some basic concepts in the context of testing of hypotheses are explained below -

11) Null Hypotheses and Alternative Hypotheses: In the context of statistical analysis,we often talk about null and alternative hypotheses. If we are to compare thesuperiority of method A with that of method B and we proceed on the assumption thatboth methods are equally good, then this assumption is termed as a null hypothesis.On the other hand, if we think that method A is superior, then it is known as analternative hypothesis.

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These are symbolically represented as:Null hypothesis = H0 and Alternative hypothesis = HaSuppose we want to test the hypothesis that the population mean is equal to the hypothesizedmean (µ H0) = 100. Then we would say that the null hypothesis is that the population mean isequal to the hypothesized mean 100 and symbolically we can express it as: H0: µ= µ H0=100If our sample results do not support this null hypothesis, we should conclude that something elseis true. What we conclude rejecting the null hypothesis is known as an alternative hypothesis. If we accept H0, then we are rejecting Ha and if we reject H0, then we are accepting Ha. For H0:µ= µ H0=100, we may consider three possible alternative hypotheses as follows:

AlternativeHypotheses

To be read as follows

Ha: µ≠µ H0 (The alternative hypothesis is that the population mean is not equal to 100i.e., it may be more or less 100)

Ha: µ>µ H0 (The alternative hypothesis is that the population mean is greater than100)

Ha: µ< µ H0 (The alternative hypothesis is that the population mean is less than 100)

The null hypotheses and the alternative hypotheses are chosen before the sample is drawn (theresearcher must avoid the error of deriving hypotheses from the data he collects and testing thehypotheses from the same data). In the choice of null hypothesis, the following considerations areusually kept in view:

1a. The alternative hypothesis is usually the one, which is to be proved, and the nullhypothesis is the one that is to be disproved. Thus a null hypothesis representsthe hypothesis we are trying to reject, while the alternative hypothesis representsall other possibilities.

2b. If the rejection of a certain hypothesis when it is actually true involves great risk, itis taken as null hypothesis, because then the probability of rejecting it when it istrue is α (the level of significance) which is chosen very small.

3c. The null hypothesis should always be a specific hypothesis i.e., it should not statean approximate value.

Generally, in hypothesis testing, we proceed on the basis of the null hypothesis, keeping thealternative hypothesis in view. Why so? The answer is that on the assumption that the nullhypothesis is true, one can assign the probabilities to different possible sample results, but thiscannot be done if we proceed with alternative hypotheses. Hence the use of null hypotheses (attimes also known as statistical hypotheses) is quite frequent.

12) The Level of Significance: This is a very important concept in the context of hypothesis testing. It is always some percentage (usually 5%), which should bechosen with great care, thought and reason. In case we take the significancelevel at 5%, then this implies that H0 will be rejected when the sampling result(i.e., observed evidence) has a less than 0.05 probability of occurring if H0 istrue. In other words, the 5% level of significance means that the researcher is

willing to take as much as 5% risk rejecting the null hypothesis when it (H0)happens to be true. Thus the significance level is the maximum value of theprobability of rejecting H0 when it is true and is usually determined in advancebefore testing the hypothesis.

23) Decision Rule or Test of Hypotheses: Given a hypothesis Ha and analternative hypothesis H0, we make a rule, which is known as a decision rule,according to which we accept H0 (i.e., reject Ha) or reject H0 (i.e., accept Ha).For instance, if H0 is that a certain lot is good (there are very few defective itemsin it), against Ha, that the lot is not good (there are many defective items in it),

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then we must decide the number of items to be tested and the criterion for accepting or rejecting the hypothesis. We might test 10 items in the lot and planour decision saying that if there are none or only 1 defective item among the 10,we will accept H0; otherwise we will reject H0 (or accept Ha). This sort of basis isknown as a decision rule.

34) Type I & II Errors: In the context of testing of hypotheses, there are basically two

types of errors that we can make. We may reject H0 when H0 is true and we mayaccept H0 when it is not true. The former is known as Type I and the latter isknown as Type II. In other words, Type I error means rejection of hypotheses,which should have been accepted, and Type II error means accepting of hypotheses, which should have been rejected. Type I error is denoted by α(alpha), also called as level of significance of test; and Type II error is denoted byβ(beta).

Decision

Accept H0 Reject H0

H0 (true) Correct decision Type I error (α error)

Ho (false) Type II error (β error) Correct decision

The probability of Type I error is usually determined in advance and is understood as the level of significance of testing the hypotheses. If type I error is fixed at 5%, it means there are about 5chances in 100 that we will reject H0 when H0 is true. We can control type I error just by fixing itat a lower level. For instance, if we fix it at 1%, we will say that the maximum probability of committing type I error would only be 0.01.But with a fixed sample size n, when we try to reduce type I error, the probability of committingtype II error increases. Both types of errors cannot be reduced simultaneously, since there is atrade-off in business situations. Decision makers decide the appropriate level of type I error byexamining the costs of penalties attached to both types of errors. If type I error involves time andtrouble of reworking a batch of chemicals that should have been accepted, whereas type II error means taking a chance that an entire group of users of this chemicals compound will bepoisoned, then in such a situation one should prefer a type I error to a type II error. As a result,one must set a very high level for type I error in one’s testing techniques of a given hypothesis.Hence, in testing of hypotheses, one must make all possible efforts to strike an adequate balancebetween Type I & Type II error.

15) Two Tailed Test & One Tailed Test: In the context of hypothesis testing, these two termsare quite important and must be clearly understood. A two-tailed test rejects the null hypothesis if,say, the sample mean is significantly higher or lower than the hypothesized value of the mean of the population. Such a test is inappropriate when we have H0: µ= µ H0 and Ha: µ≠µ H0 whichmay µ>µ H0 or µ<µ H0. If significance level is 5 % and the two-tailed test is to be applied, theprobability of the rejection area will be 0.05 (equally split on both tails of the curve as 0.025) andthat of the acceptance region will be 0.95. If we take µ = 100 and if our sample mean deviatessignificantly from µ, in that case we shall accept the null hypothesis. But there are situations whenonly a one-tailed test is considered appropriate. A one-tailed test would be used when we are totest, say, whether the population mean is either lower or higher than some hypothesized value.Parametric statistics is a branch of statistics that assumes data come from a type of probabilitydistribution and makes inferences about the parameters of the distribution most well knownelementary statistical methods are parametric.Generally speaking parametric methods make more assumptions than non-parametricmethods. If those extra assumptions are correct, parametric methods can produce more accurateand precise estimates. They are said to have more statistical power. However, if thoseassumptions are incorrect, parametric methods can be very misleading. For that reason they areoften not considered robust. On the other hand, parametric formulae are often simpler to write

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down and faster to compute. In some, but definitely not all cases, their simplicity makes up for their non-robustness, especially if care is taken to examine diagnostic statistics.Because parametric statistics require a probability distribution, they are not distribution-free.Non-parametric models differ from parametric models in that the model structure is notspecified a priori but is instead determined from data. The term nonparametric is not meant toimply that such models completely lack parameters but that the number and nature of theparameters are flexible and not fixed in advance.Kernel density estimation provides better estimates of the density than histograms.Nonparametric regression and semi parametric regression methods have been developed basedon kernels, splines, and wavelets.Data Envelopment Analysis provides efficiency coefficients similar to those obtainedby Multivariate Analysis without any distributional assumption.

Q 3. Explain the difference between a causal relationship and correlation, with an exampleof each. What are the possible reasons for a correlation between two variables?

Ans.: Correlation: The correlation is knowing what the consumer wants, and providing it.Marketing research looks at trends in sales and studies all of the variables, i.e. price, color,availability, and styles, and the best way to give the customer what he or she wants. If you cangive the customer what they want, they will buy, and let friends and family know where they got it.

Making them happy makes the money.

Casual relationship Marketing  was first defined as a form of marketing developed from directresponse marketing campaigns, which emphasizes customer retention and satisfaction, rather than a dominant focus on sales transactions.

As a practice, Relationship Marketing differs from other forms of marketing in that it recognizesthe long term value of customer relationships and extends communication beyond intrusiveadvertising and sales promotional messages.

With the growth of the internet and mobile platforms, Relationship Marketing has continued to

evolve and move forward as technology opens more collaborative and social communicationchannels. This includes tools for managing relationships with customers that goes beyond simpledemographic and customer service data. Relationship Marketing extends to include InboundMarketing efforts (a combination of search optimization and Strategic Content), PR, Social Mediaand Application Development.

Just like Customer relationship management(CRM), Relationship Marketing is a broadlyrecognized, widely-implemented strategy for managing and nurturing a company’s interactionswith clients and sales prospects. It also involves using technology to, organize, synchronizebusiness processes (principally sales and marketing activities) and most importantly, automatethose marketing and communication activities on concrete marketing sequences that could run inautopilot (also known as marketing sequences). The overall goals are to find, attract, and win newclients, nurture and retain those the company already has, entice former clients back into the fold,and reduce the costs of marketing and client service. [1] Once simply a label for a category of software tools, today, it generally denotes a company-wide business strategy embracing all client-facing departments and even beyond. When an implementation is effective, people, processes,and technology work in synergy to increase profitability, and reduce operational costs

Reasons for a correlation between two variables: Chance association, (the relationship is dueto chance) or causative association (one variable causes the other).

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The information given by a correlation coefficient is not enough to define the dependencestructure between random variables. The correlation coefficient completely defines thedependence structure only in very particular cases, for example when the distribution is amultivariate normal distribution. (See diagram above.) In the case of elliptic distributions itcharacterizes the (hyper-)ellipses of equal density, however, it does not completely characterizethe dependence structure (for example, a multivariate t-distribution's degrees of freedomdetermine the level of tail dependence).

Distance correlation and Brownian covariance / Brownian correlation [8][9] were introduced toaddress the deficiency of Pearson's correlation that it can be zero for dependent randomvariables; zero distance correlation and zero Brownian correlation imply independence.

The correlation ratio is able to detect almost any functional dependency, or the entropy-basedmutual information/total correlation which is capable of detecting even more generaldependencies. The latter are sometimes referred to as multi-moment correlation measures, incomparison to those that consider only 2nd moment (pairwise or quadratic) dependence.

The polychoric correlation is another correlation applied to ordinal data that aims to estimate thecorrelation between theorised latent variables.

One way to capture a more complete view of dependence structure is to consider a copulabetween them.

Q 4. Briefly explain any two factors that affect the choice of a sampling technique. Whatare the characteristics of a good sample?

Ans.: The difference between non-probability and probability sampling is that non-probabilitysampling does not involve random selection and probability sampling does. Does that mean thatnon-probability samples aren't representative of the population? Not necessarily. But it doesmean that non-probability samples cannot depend upon the rationale of probability theory. Atleast with a probabilistic sample, we know the odds or probability that we have represented thepopulation well. We are able to estimate confidence intervals for the statistic. With non-probabilitysamples, we may or may not represent the population well, and it will often be hard for us to knowhow well we've done so. In general, researchers prefer probabilistic or random sampling methodsover non probabilistic ones, and consider them to be more accurate and rigorous. However, inapplied social research there may be circumstances where it is not feasible, practical or theoretically sensible to do random sampling. Here, we consider a wide range of non-probabilisticalternatives.

We can divide non-probability sampling methods into two broad types:Accidental or purposive.

Most sampling methods are purposive in nature because we usually approach thesampling problem with a specific plan in mind. The most important distinctions among these typesof sampling methods are the ones between the different types of purposive sampling approaches.

Accidental, Haphazard or Convenience Sampling 

One of the most common methods of sampling goes under the various titles listed here. Iwould include in this category the traditional "man on the street" (of course, now it's probably the"person on the street") interviews conducted frequently by television news programs to get a

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quick (although non representative) reading of public opinion. I would also argue that the typicaluse of college students in much psychological research is primarily a matter of convenience. (Youdon't really believe that psychologists use college students because they believe they'rerepresentative of the population at large, do you?). In clinical practice, we might use clients whoare available to us as our sample. In many research contexts, we sample simply by asking for volunteers. Clearly, the problem with all of these types of samples is that we have no evidencethat they are representative of the populations we're interested in generalizing to -- and in manycases we would clearly suspect that they are not.

Purposive Sampling 

In purposive sampling, we sample with a purpose in mind. We usually would have one or more specific predefined groups we are seeking. For instance, have you ever run into people in amall or on the street who are carrying a clipboard and who are stopping various people andasking if they could interview them? Most likely they are conducting a purposive sample (andmost likely they are engaged in market research). They might be looking for Caucasian femalesbetween 30-40 years old. They size up the people passing by and anyone who looks to be in thatcategory they stop to ask if they will participate. One of the first things they're likely to do is verifythat the respondent does in fact meet the criteria for being in the sample. Purposive sampling canbe very useful for situations where you need to reach a targeted sample quickly and wheresampling for proportionality is not the primary concern. With a purposive sample, you are likely toget the opinions of your target population, but you are also likely to overweight subgroups in your population that are more readily accessible.

All of the methods that follow can be considered subcategories of purposive samplingmethods. We might sample for specific groups or types of people as in modal instance, expert, or quota sampling. We might sample for diversity as in heterogeneity sampling. Or, we mightcapitalize on informal social networks to identify specific respondents who are hard to locateotherwise, as in snowball sampling. In all of these methods we know what we want -- we aresampling with a purpose.

• Modal Instance SamplingIn statistics, the mode is the most frequently occurring value in a distribution. In sampling, whenwe do a modal instance sample, we are sampling the most frequent case, or the "typical" case. Ina lot of informal public opinion polls, for instance, they interview a "typical" voter. There are anumber of problems with this sampling approach. First, how do we know what the "typical" or "modal" case is? We could say that the modal voter is a person who is of average age,educational level, and income in the population. But, it's not clear that using the averages of theseis the fairest (consider the skewed distribution of income, for instance). And, how do you knowthat those three variables -- age, education, income -- are the only or even the most relevant for classifying the typical voter? What if religion or ethnicity is an important discriminator? Clearly,modal instance sampling is only sensible for informal sampling contexts.

• Expert SamplingExpert sampling involves the assembling of a sample of persons with known or demonstrableexperience and expertise in some area. Often, we convene such a sample under the auspices of a "panel of experts." There are actually two reasons you might do expert sampling. First, becauseit would be the best way to elicit the views of persons who have specific expertise. In this case,

expert sampling is essentially just a specific sub case of purposive sampling. But the other reasonyou might use expert sampling is to provide evidence for the validity of another samplingapproach you've chosen. For instance, let's say you do modal instance sampling and areconcerned that the criteria you used for defining the modal instance are subject to criticism. Youmight convene an expert panel consisting of persons with acknowledged experience and insightinto that field or topic and ask them to examine your modal definitions and comment on their appropriateness and validity. The advantage of doing this is that you aren't out on your own tryingto defend your decisions -- you have some acknowledged experts to back you. The disadvantageis that even the experts can be, and often are, wrong.

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• Quota SamplingIn quota sampling, you select people non-randomly according to some fixed quota. There are twotypes of quota sampling: proportional and non proportional . In proportional quota sampling youwant to represent the major characteristics of the population by sampling a proportional amountof each. For instance, if you know the population has 40% women and 60% men, and that you

want a total sample size of 100, you will continue sampling until you get those percentages andthen you will stop. So, if you've already got the 40 women for your sample, but not the sixty men,you will continue to sample men but even if legitimate women respondents come along, you willnot sample them because you have already "met your quota." The problem here (as in muchpurposive sampling) is that you have to decide the specific characteristics on which you will basethe quota. Will it be by gender, age, education race, religion, etc.?Non-proportional quota sampling is a bit less restrictive. In this method, you specify theminimum number of sampled units you want in each category. Here, you're not concerned withhaving numbers that match the proportions in the population. Instead, you simply want to haveenough to assure that you will be able to talk about even small groups in the population. Thismethod is the non-probabilistic analogue of stratified random sampling in that it is typically usedto assure that smaller groups are adequately represented in your sample.

• Heterogeneity SamplingWe sample for heterogeneity when we want to include all opinions or views, and we aren'tconcerned about representing these views proportionately. Another term for this is sampling for diversity . In many brainstorming or nominal group processes (including concept mapping), wewould use some form of heterogeneity sampling because our primary interest is in getting broadspectrum of ideas, not identifying the "average" or "modal instance" ones. In effect, what wewould like to be sampling is not people, but ideas. We imagine that there is a universe of allpossible ideas relevant to some topic and that we want to sample this population, not thepopulation of people who have the ideas. Clearly, in order to get all of the ideas, and especiallythe "outlier" or unusual ones, we have to include a broad and diverse range of participants.Heterogeneity sampling is, in this sense, almost the opposite of modal instance sampling.

• Snowball SamplingIn snowball sampling, you begin by identifying someone who meets the criteria for inclusion in

your study. You then ask them to recommend others who they may know who also meet thecriteria. Although this method would hardly lead to representative samples, there are times whenit may be the best method available. Snowball sampling is especially useful when you are tryingto reach populations that are inaccessible or hard to find. For instance, if you are studying thehomeless, you are not likely to be able to find good lists of homeless people within a specificgeographical area. However, if you go to that area and identify one or two, you may find that theyknow very well whom the other homeless people in their vicinity are and how you can find them.Characteristics of good Sample: The decision process is a complicated one. The researcher has to first identify the limiting factor or factors and must judiciously balance the conflictingfactors. The various criteria governing the choice of the sampling technique are:

11. Purpose of the Survey: What does the researcher aim at? If he intends togeneralize the findings based on the sample survey to the population, then anappropriate probability sampling method must be selected. The choice of a particular 

type of probability sampling depends on the geographical area of the survey and thesize and the nature of the population under study.

22.Measurability: The application of statistical inference theory requires computation of the sampling error from the sample itself. Only probability samples allow suchcomputation. Hence, where the research objective requires statistical inference, thesample should be drawn by applying simple random sampling method or stratifiedrandom sampling method, depending on whether the population is homogenous or heterogeneous.

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33.Degree of Precision: Should the results of the survey be very precise, or could evenrough results serve the purpose? The desired level of precision is one of the criteriafor sampling method selection. Where a high degree of precision of results is desired,probability sampling should be used. Where even crude results would serve thepurpose (E.g., marketing surveys, readership surveys etc), any convenient non-random sampling like quota sampling would be enough.

44. Information about Population: How much information is available about thepopulation to be studied? Where no list of population and no information about itsnature are available, it is difficult to apply a probability sampling method. Then anexploratory study with non-probability sampling may be done to gain a better idea of the population. After gaining sufficient knowledge about the population through theexploratory study, an appropriate probability sampling design may be adopted.

55. The Nature of the Population: In terms of the variables to be studied, is thepopulation homogenous or heterogeneous? In the case of a homogenous population,even simple random sampling will give a representative sample. If the population isheterogeneous, stratified random sampling is appropriate.

66. Geographical Area of the Study and the Size of the Population: If the areacovered by a survey is very large and the size of the population is quite large, multi-stage cluster sampling would be appropriate. But if the area and the size of the

population are small, single stage probability sampling methods could be used.77. Financial Resources: If the available finance is limited, it may become necessary to

choose a less costly sampling plan like multistage cluster sampling, or even quotasampling as a compromise. However, if the objectives of the study and the desiredlevel of precision cannot be attained within the stipulated budget, there is noalternative but to give up the proposed survey. Where the finance is not a constraint,a researcher can choose the most appropriate method of sampling that fits theresearch objective and the nature of population.

88. Time Limitation: The time limit within which the research project should becompleted restricts the choice of a sampling method. Then, as a compromise, it maybecome necessary to choose less time consuming methods like simple randomsampling, instead of stratified sampling/sampling with probability proportional to size;or multi-stage cluster sampling, instead of single-stage sampling of elements. Of 

course, the precision has to be sacrificed to some extent.99. Economy: It should be another criterion in choosing the sampling method. It means

achieving the desired level of precision at minimum cost. A sample is economical if the precision per unit cost is high, or the cost per unit of variance is low. The abovecriteria frequently conflict with each other and the researcher must balance and blendthem to obtain a good sampling plan. The chosen plan thus represents an adaptationof the sampling theory to the available facilities and resources. That is, it represents acompromise between idealism and feasibility. One should use simple workablemethods, instead of unduly elaborate and complicated techniques.

Q 5. Select any topic for research and explain how you will use both secondary andprimary sources to gather the required information.

Ans.: Primary Sources of DataPrimary sources are original sources from which the researcher directly collects data that has notbeen previously collected, e.g., collection of data directly by the researcher on brand awareness,brand preference, and brand loyalty and other aspects of consumer behavior, from a sample of consumers by interviewing them. Primary data is first hand information collected through various

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methods such as surveys, experiments and observation, for the purposes of the projectimmediately at hand.The advantages of primary data are –

1 It is unique to a particular research study

2 It is recent information, unlike published information that is already available

The disadvantages are –1 It is expensive to collect, compared to gathering information from available  sources

2 Data collection is a time consuming process

3 It requires trained interviewers and investigators

2 Secondary Sources of DataThese are sources containing data, which has been collected and compiled for another purpose.Secondary sources may be internal sources, such as annual reports, financial statements, salesreports, inventory records, minutes of meetings and other information that is available within thefirm, in the form of a marketing information system. They may also be external sources, such asgovernment agencies (e.g. census reports, reports of government departments), publishedsources (annual reports of currency and finance published by the Reserve Bank of India,

publications of international organizations such as the UN, World Bank and InternationalMonetary Fund, trade and financial journals, etc.), trade associations (e.g. Chambers of Commerce) and commercial services (outside suppliers of information).Methods of Data Collection:The researcher directly collects primary data from its original sources. In this case, the researcher can collect the required data precisely according to his research needs and he can collect themwhen he wants and in the form that he needs it. But the collection of primary data is costly andtime consuming. Yet, for several types of social science research, required data is not availablefrom secondary sources and it has to be directly gathered from the primary sources.Primary data has to be gathered in cases where the available data is inappropriate, inadequate or obsolete. It includes: socio economic surveys, social anthropological studies of rural communitiesand tribal communities, sociological studies of social problems and social institutions, marketingresearch, leadership studies, opinion polls, attitudinal surveys, radio listening and T.V. viewingsurveys, knowledge-awareness practice (KAP) studies, farm management studies, businessmanagement studies etc.There are various methods of primary data collection, including surveys, audits and panels,observation and experiments.1 Survey ResearchA survey is a fact-finding study. It is a method of research involving collection of data directly froma population or a sample at a particular time. A survey has certain characteristics:1 It is always conducted in a natural setting. It is a field study.

2 It seeks responses directly from the respondents.

3 It can cover a very large population.

4 It may include an extensive study or an intensive study

5 It covers a definite geographical area.

A survey involves the following steps -

1 Selection of a problem and its formulation

2 Preparation of the research design

3 Operation concepts and construction of measuring indexes and scales

4 Sampling

5 Construction of tools for data collection

6 Field work and collection of data

7 Processing of data and tabulation

8 Analysis of data

9 Reporting

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There are four basic survey methods, which include:1 Personal interview

2 Telephone interview

3 Mail survey and

4 Fax survey

Personal InterviewPersonal interviewing is one of the prominent methods of data collection. It may be defined as atwo-way systematic conversation between an investigator and an informant, initiated for obtaininginformation relevant to a specific study. It involves not only conversation, but also learning fromthe respondent’s gestures, facial expressions and pauses, and his environment.Interviewing may be used either as a main method or as a supplementary one in studies of persons. Interviewing is the only suitable method for gathering information from illiterate or lesseducated respondents. It is useful for collecting a wide range of data, from factual demographicdata to highly personal and intimate information relating to a person’s opinions, attitudes, values,beliefs, experiences and future intentions. Interviewing is appropriate when qualitative informationis required, or probing is necessary to draw out the respondent fully. Where the area covered for the survey is compact, or when a sufficient number of qualified interviewers are available,personal interview is feasible.Interview is often superior to other data-gathering methods. People are usually more willing to talk

than to write. Once rapport is established, even confidential information may be obtained. Itpermits probing into the context and reasons for answers to questions.Interview can add flesh to statistical information. It enables the investigator to grasp thebehavioral context of the data furnished by the respondents. It permits the investigator to seekclarifications and brings to the forefront those questions, which for some reason or the other therespondents do not want to answer. Interviewing as a method of data collection has certaincharacteristics. They are:

1. The participants – the interviewer and the respondent – are strangers;hence, the investigator has to get himself/herself introduced to therespondent in an appropriate manner.

2. The relationship between the participants is a transitory one. It has afixed beginning and termination points. The interview proper is a fleeting,momentary experience for them.

3. The interview is not a mere casual conversational exchange, but aconversation with a specific purpose, viz., obtaining information relevantto a study.

4. The interview is a mode of obtaining verbal answers to questions putverbally.

5. The interaction between the interviewer and the respondent need notnecessarily be on a face-to-face basis, because the interview can also beconducted over the telephone.

6. Although the interview is usually a conversation between two persons, itneed not be limited to a single respondent. It can also be conducted witha group of persons, such as family members, or a group of children, or agroup of customers, depending on the requirements of the study.

7. The interview is an interactive process. The interaction between the

interviewer and the respondent depends upon how they perceive eachother.8. The respondent reacts to the interviewer’s appearance, behavior,

gestures, facial expression and intonation, his perception of the thrust of the questions and his own personal needs. As far as possible, theinterviewer should try to be closer to the social-economic level of therespondents.

9. The investigator records information furnished by the respondent in theinterview. This poses a problem of seeing that recording does notinterfere with the tempo of conversation.

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10. Interviewing is not a standardized process like that of a chemicaltechnician; it is rather a flexible, psychological process.

3 Telephone Interviewing Telephone interviewing is a non-personal method of data collection. Itmay be used as a major method or as a supplementary method. It will be useful in the followingsituations:

11. When the universe is composed of those persons whose names arelisted in telephone directories, e.g. business houses, businessexecutives, doctors and other professionals.

12. When the study requires responses to five or six simple questions, e.g. aradio or television program survey.

13. When the survey must be conducted in a very short period of time,provided the units of study are listed in the telephone directory.

14. When the subject is interesting or important to respondents, e.g. a surveyrelating to trade conducted by a trade association or a chamber of commerce, a survey relating to a profession conducted by the concernedprofessional association.

15. When the respondents are widely scattered and when there are manycall backs to make.

4 Group Interviews A group interview may be defined as a method of collecting primary data inwhich a number of individuals with a common interest interact with each other. In a personal

interview, the flow of information is multi dimensional. The group may consist of about six to eightindividuals with a common interest. The interviewer acts as the discussion leader. Freediscussion is encouraged on some aspect of the subject under study. The discussion leader stimulates the group members to interact with each other. The desired information may beobtained through self-administered questionnaire or interview, with the discussion serving as aguide to ensure consideration of the areas of concern. In particular, the interviewers look for evidence of common elements of attitudes, beliefs, intentions and opinions among individuals inthe group. At the same time, he must be aware that a single comment by a member can provideimportant insight. Samples for group interviews can be obtained through schools, clubs and other organized groups.5 Mail Survey The mail survey is another method of collecting primary data. This methodinvolves sending questionnaires to the respondents with a request to complete them and returnthem by post. This can be used in the case of educated respondents only. The mail

questionnaires should be simple so that the respondents can easily understand the questions andanswer them. It should preferably contain mostly closed-ended and multiple choice questions, sothat it could be completed within a few minutes. The distinctive feature of the mail survey is thatthe questionnaire is self-administered by the respondents themselves and the responses arerecorded by them and not by the investigator, as in the case of personal interview method. It doesnot involve face-to-face conversation between the investigator and the respondent.Communication is carried out only in writing and this requires more cooperation from therespondents than verbal communication. The researcher should prepare a mailing list of theselected respondents, by collecting the addresses from the telephone directory of the associationor organization to which they belong. The following procedures should be followed - a covering  letter should accompany a copy of the questionnaire. It must explain to the respondent thepurpose of the study and the importance of his cooperation to the success of the project. Anonymity must be assured. The sponsor’s identity may be revealed. However, when such  

information may bias the result, it is not desirable to reveal it. In this case, a disguisedorganization name may be used. A self-addressed stamped envelope should be enclosed in  the covering letter.

1 After a few days from the date of mailing the questionnaires to the respondents, the  researcher can expect the return of completed ones from them. The progress in return may bewatched and at the appropriate stage, follow-up efforts can be made.

The response rate in mail surveys is generally very low in developing countries like India. Certaintechniques have to be adopted to increase the response rate. They are:

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11. Quality printing: The questionnaire may be neatly printed on quality light colored paper,so as to attract the attention of the respondent.

22. Covering letter: The covering letter should be couched in a pleasant style, so as toattract and hold the interest of the respondent. It must anticipate objections and answer them briefly. It is desirable to address the respondent by name.

33. Advance information: Advance information can be provided to potential respondents by

a telephone call, or advance notice in the newsletter of the concerned organization, or bya letter. Such preliminary contact with potential respondents is more successful thanfollow-up efforts.

44. Incentives: Money, stamps for collection and other incentives are also used to inducerespondents to complete and return the mail questionnaire.

55. Follow-up-contacts: In the case of respondents belonging to an organization, they maybe approached through someone in that organization known as the researcher.

66. Larger sample size: A larger sample may be drawn than the estimated sample size. For example, if the required sample size is 1000, a sample of 1500 may be drawn. This mayhelp the researcher to secure an effective sample size closer to the required size.

78Q 6. Case Study: You are engaged to carry out a market survey on behalf of a leading

Newspaper that is keen to increase its circulation in Bangalore City, in order toascertain reader habits and interests. Develop a title for the study; define theresearch problem and the objectives or questions to be answered by the study.

Ans.: Title: Newspaper reading choices

Research problem: A research problem is the situation that causes the researcher to feelapprehensive, confused and ill at ease. It is the demarcation of a problem area within a certaincontext involving the WHO or WHAT, the WHERE, the WHEN and the WHY of the problemsituation.

There are many problem situations that may give rise to research. Three sources usually

contribute to problem identification. Own experience or the experience of others may be a sourceof problem supply. A second source could be scientific literature. You may read about certainfindings and notice that a certain field was not covered. This could lead to a research problem.Theories could be a third source. Shortcomings in theories could be researched.

Research can thus be aimed at clarifying or substantiating an existing theory, at clarifyingcontradictory findings, at correcting a faulty methodology, at correcting the inadequate or unsuitable use of statistical techniques, at reconciling conflicting opinions, or at solving existingpractical problems

Types of questions to be asked :For more than 35 years, the news about newspapers andyoung readers has been mostly bad for the newspaper industry. Long before any competitionfrom cable television or Nintendo, American newspaper publishers were worrying about declining

readership among the young.

As early as 1960, at least 20 years prior to Music Television (MTV) or the Internet, mediaresearch scholars1 began to focus their studies on young adult readers' decreasing interest innewspaper content. The concern over a declining youth market preceded and perhapsforeshadowed today's fretting over market penetration. Even where circulation has grown or stayed stable, there is rising concern over penetration, defined as the percentage of occupiedhouseholds in a geographic market that are served by a newspaper.2 Simply put, populationgrowth is occurring more rapidly than newspaper readership in most communities.

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This study looks at trends in newspaper readership among the 18-to-34 age group and examinessome of the choices young adults make when reading newspapers.

One of the underlying concerns behind the decline in youth newspaper reading is the question of how young people view the newspaper. A number of studies explored how young readersevaluate and use newspaper content.

Comparing reader content preferences over a 10-year period, Gerald Stone and TimothyBoudreau found differences between readers ages 18-34 and those 35-plus.16 Younger readersshowed increased interest in national news, weather, sports, and classified advertisements over the decade between 1984 and 1994, while older readers ranked weather, editorials, and foodadvertisements higher. Interest in international news and letters to the editor was less amongyounger readers, while older readers showed less interest in reports of births, obituaries, andmarriages.

David Atkin explored the influence of telecommunication technology on newspaper readershipamong students in undergraduate media courses.17 He reported that computer-relatedtechnologies, including electronic mail and computer networks, were unrelated to newspaper readership. The study found that newspaper subscribers preferred print formats over electronic.

In a study of younger, school-age children, Brian Brooks and James Kropp found that electronicnewspapers could persuade children to become news consumers, but that young readers wouldchoose an electronic newspaper over a printed one.18

In an exploration of leisure reading among college students, Leo Jeffres and Atkin assesseddimensions of interest in newspapers, magazines, and books,19 exploring the influence of mediause, non-media leisure, and academic major on newspaper content preferences. The studydiscovered that overall newspaper readership was positively related to students' focus onentertainment, job / travel information, and public affairs. However, the students' preference for reading as a leisure-time activity was related only to a public affairs focus. Content preferencesfor newspapers and other print media were related. The researchers found no significantdifferences in readership among various academic majors, or by gender, though there was aslight correlation between age and the public affairs readership index, with older readers more

interested in news about public affairs.

Methodology

Sample

Participants in this study (N=267) were students enrolled in 100- and 200-level English courses ata midwestern public university. Courses that comprise the framework for this sample wereselected because they could fulfill basic studies requirements for all majors. A basic studiescourse is one that is listed within the core curriculum required for all students. The researcher obtained permission from seven professors to distribute questionnaires in the eight classes duringregularly scheduled class periods. The students' participation was voluntary; two studentsdeclined. The goal of this sampling procedure was to reach a cross-section of students

representing various fields of study. In all, 53 majors were represented.

Of the 267 students who participated in the study, 65 (24.3 percent) were male and 177 (66.3percent) were female. A total of 25 participants chose not to divulge their genders. Ages rangedfrom 17 to 56, with a mean age of 23.6 years. This mean does not include the 32 respondentswho declined to give their ages. A total of 157 participants (58.8 percent) said they were of theCaucasian race, 59 (22.1 percent) African American, 10 (3.8 percent) Asian, five (1.9 percent)African/Native American, two (.8 percent) Hispanic, two (.8 percent) Native American, and one (.4percent) Arabic. Most (214) of the students were enrolled full time, whereas a few (28) were part-

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time students. The class rank breakdown was: freshmen, 45 (16.9 percent); sophomores, 15 (5.6percent); juniors, 33 (12.4 percent); seniors, 133 (49.8 percent); and graduate students, 16 (6percent).

Procedure

After two pre-tests and revisions, questionnaires were distributed and collected by theinvestigator. In each of the eight classes, the researcher introduced herself to the students as ajournalism professor who was conducting a study on students' use of newspapers and other media. Each questionnaire included a cover letter with the researcher's name, address, andphone number. The researcher provided pencils and was available to answer questions if anyoneneeded further assistance. The average time spent on the questionnaires was 20 minutes, withsome individual students taking as long as an hour. Approximately six students asked to take thequestionnaires home to finish. They returned the questionnaires to the researcher's mailboxwithin a couple of day.

  Assignment Set- 2

Q 1.Discuss the relative advantages and disadvantages of the different methods of distributing questionnaires to the respondents of a study.

Ans.: There are some alternative methods of distributing questionnaires to the respondents.They are:1) Personal delivery,2) Attaching the questionnaire to a product,3) Advertising the questionnaire in a newspaper or magazine, and4) News-stand inserts.Personal delivery: The researcher or his assistant may deliver the questionnaires to thepotential respondents, with a request to complete them at their convenience. After a day or two,the completed questionnaires can be collected from them. Often referred to as the self-

administered questionnaire method, it combines the advantages of the personal interview and themail survey. Alternatively, the questionnaires may be delivered in person and the respondentsmay return the completed questionnaires through mail.Attaching questionnaire to a product: A firm test marketing a product may attach aquestionnaire to a product and request the buyer to complete it and mail it back to the firm. A giftor a discount coupon usually rewards the respondent.Advertising the questionnaire: The questionnaire with the instructions for completion may beadvertised on a page of a magazine or in a section of newspapers. The potential respondentcompletes it, tears it out and mails it to the advertiser. For example, the committee of BanksCustomer Services used this method for collecting information from the customers of commercialbanks in India. This method may be useful for large-scale studies on topics of common interest.Newsstand inserts: This method involves inserting the covering letter, questionnaire and self addressed reply-paid envelope into a random sample of newsstand copies of a newspaper or 

magazine.Advantages and Disadvantages:The advantages of Questionnaire are:

this method facilitates collection of more accurate data for longitudinal studies than any other   method, because under this method, the event or action is reported soon after its occurrence.

this method makes it possible to have before and after designs made for field based studies.  For example, the effect of public relations or advertising campaigns or welfare measures can bemeasured by collecting data before, during and after the campaign.

the panel method offers a good way of studying trends in events, behavior or attitudes. For   example, a panel enables a market researcher to study how brand preferences change from

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month to month; it enables an economics researcher to study how employment, income andexpenditure of agricultural laborers change from month to month; a political scientist can studythe shifts in inclinations of voters and the causative influential factors during an election. It is alsopossible to find out how the constituency of the various economic and social strata of societychanges through time and so on.

A panel study also provides evidence on the causal relationship between variables. For   example, a cross sectional study of employees may show an association between their attitude totheir jobs and their positions in the organization, but it does not indicate as to which comes first -favorable attitude or promotion. A panel study can provide data for finding an answer to thisquestion.

It facilities depth interviewing, because panel members become well acquainted with the field  workers and will be willing to allow probing interviews.

The major limitations or problems of Questionnaire method are:this method is very expensive. The selection of panel members, the payment of premiums,  

periodic training of investigators and supervisors, and the costs involved in replacing dropouts, alladd to the expenditure.

it is often difficult to set up a representative panel and to keep it representative. Many persons  may be unwilling to participate in a panel study. In the course of the study, there may be frequentdropouts. Persons with similar characteristics may replace the dropouts. However, there is no

guarantee that the emerging panel would be representative.A real danger with the panel method is “panel conditioning” i.e., the risk that repeated  

interviews may sensitize the panel members and they become untypical, as a result of being onthe panel. For example, the members of a panel study of political opinions may try to appear consistent in the views they express on consecutive occasions. In such cases, the panelbecomes untypical of the population it was selected to represent. One possible safeguard topanel conditioning is to give members of a panel only a limited panel life and then to replace themwith persons taken randomly from a reserve list.

the quality of reporting may tend to decline, due to decreasing interest, after a panel has been  in operation for some time. Cheating by panel members or investigators may be a problem insome cases.

Q 2. In processing data, what is the difference between measures of central tendency andmeasures of dispersion? What is the most important measure of central tendency anddispersion?

Ans.: Measures of Central tendency:Arithmetic MeanThe arithmetic mean is the most common measure of central tendency. It simply the sum of thenumbers divided by the number of numbers. The symbol m is used for the mean of a population.The symbol M is used for the mean of a sample. The formula for m is shown below: m=ΣX

NWhere ΣX is the sum of all the numbers in the numbers in the sample and N is the number of 

numbers in the sample. As an example, the mean of the numbers 1+2+3+6+8=20

5

=4 regardless of whether the numbers constitute the entire population or just a sample fromthe population.

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The table, Number of touchdown passes, shows the number of touchdown (TD) passes thrownby each of the 31 teams in the National Football League in the 2000 season. The mean number of touchdown passes thrown is 20.4516 as shown below. m=ΣX

N

=

63431

=20.451637 33 33 32 29 28 28 2322 22 22 21 21 21 20 2019 19 18 18 18 18 16 1514 14 14 12 12 9 6Table 1: Number of touchdown passes

Although the arithmetic mean is not the only "mean" (there is also a geometric mean), it is by far the most commonly used. Therefore, if the term "mean" is used without specifying whether it isthe arithmetic mean, the geometric mean, or some other mean, it is assumed to refer to thearithmetic mean.MedianThe median is also a frequently used measure of central tendency. The median is the midpoint of a distribution: the same number of scores is above the median as below it. For the data in thetable, Number of touchdown passes, there are 31 scores. The 16th highest score (which equals20) is the median because there are 15 scores below the 16th score and 15 scores above the16th score. The median can also be thought of as the 50th percentile. Let's return to the made up example of the quiz on which you made a three discussed previouslyin the module Introduction to Central Tendency and shown in Table 2.

Student Dataset 1 Dataset 2 Dataset 3

You 3 3 3John's 3 4 2Maria's 3 4 2Shareecia's 3 4 2Luther's 3 5 1

Table 2: Three possible datasets for the 5-point make-up quizFor Dataset 1, the median is three, the same as your score. For Dataset 2, the median is 4.Therefore, your score is below the median. This means you are in the lower half of the class.Finally for Dataset 3, the median is 2. For this dataset, your score is above the median andtherefore in the upper half of the distribution.Computation of the Median: When there is an odd number of numbers, the median is simply themiddle number. For example, the median of 2, 4, and 7 is 4. When there is an even number of numbers, the median is the mean of the two middle numbers. Thus, the median of the numbers 2,4, 7, 12 is4+7

2

=5.5.ModeThe mode is the most frequently occurring value. For the data in the table, Number of touchdownpasses, the mode is 18 since more teams (4) had 18 touchdown passes than any other number of touchdown passes. With continuous data such as response time measured to many decimals,the frequency of each value is one since no two scores will be exactly the same (see discussionof continuous variables). Therefore the mode of continuous data is normally computed from agrouped frequency distribution. The Grouped frequency distribution table shows a groupedfrequency distribution for the target response time data. Since the interval with the highestfrequency is 600-700, the mode is the middle of that interval (650).

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Range Frequency

500-600 3600-700 6700-800 5800-900 5900-1000 0

1000-1100 1Table 3: Grouped frequency distribution

Measures of Dispersion: A measure of statistical dispersion is a real number that is zero if allthe data are identical, and increases as the data becomes more diverse. It cannot be less thanzero.

Most measures of dispersion have the same scale as the quantity being measured. In other words, if the measurements have units, such as metres or seconds, the measure of dispersionhas the same units. Such measures of dispersion include:

• Standard deviation• Interquartile range • Range• Mean difference • Median absolute deviation • Average absolute deviation (or simply called average deviation)• Distance standard deviation

These are frequently used (together with scale factors) as estimators of scale parameters, inwhich capacity they are called estimates of scale.

All the above measures of statistical dispersion have the useful property that they are location-invariant, as well as linear in scale. So if a random variable X has a dispersion of S X  then a linear 

transformation Y = aX + b for real a and b should have dispersion S Y = |a|S X .

Other measures of dispersion are dimensionless (scale-free). In other words, they have nounits even if the variable itself has units. These include:

• Coefficient of variation • Quartile coefficient of dispersion• Relative mean difference, equal to twice the Gini coefficient

There are other measures of dispersion:

• Variance (the square of the standard deviation) location-invariant but not linear in

scale.• Variance-to-mean ratio mostly used for count data when the term coefficient of 

dispersion is used and when this ratio is dimensionless, as count data are themselvesdimensionless: otherwise this is not scale-free.

Some measures of dispersion have specialized purposes, among them the Allan variance andthe Hadamard variance.

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For categorical variables, it is less common to measure dispersion by a single number. Seequalitative variation. One measure that does so is the discrete entropy.

Sources of statistical dispersion

In the physical sciences, such variability may result only from random measurement errors:

instrument measurements are often not perfectly precise, i.e., reproducible. One may assumethat the quantity being measured is unchanging and stable, and that the variation betweenmeasurements is due to observational error .

In the biological sciences, this assumption is false: the variation observed might be intrinsic to thephenomenon: distinct members of a population differ greatly. This is also seen in the arena of manufactured products; even there, the meticulous scientist finds variation.The simple model of astable quantity is preferred when it is tenable. Each phenomenon must be examined to see if itwarrants such a simplification.

Q 3. What are the characteristics of a good research design? Explain how the researchdesign for exploratory studies is different from the research design for descriptive anddiagnostic studies.

Ans.: Good research design:Much contemporary social research is devoted to examiningwhether a program, treatment, or manipulation causes some outcome or result. For example, wemight wish to know whether a new educational program causes subsequent achievement scoregains, whether a special work release program for prisoners causes lower recidivism rates,whether a novel drug causes a reduction in symptoms, and so on. Cook and Campbell (1979)argue that three conditions must be met before we can infer that such a cause-effect relationexists:

1. Covariation. Changes in the presumed cause must be related to changes in thepresumed effect. Thus, if we introduce, remove, or change the level of a treatment or program, we should observe some change in the outcome measures.

2.Temporal Precedence. The presumed cause must occur prior to the presumed effect.

3. No Plausible Alternative Explanations. The presumed cause must be the onlyreasonable explanation for changes in the outcome measures. If there are other factors,which could be responsible for changes in the outcome measures, we cannot beconfident that the presumed cause-effect relationship is correct.

In most social research the third condition is the most difficult to meet. Any number of factorsother than the treatment or program could cause changes in outcome measures. Campbell andStanley (1966) and later, Cook and Campbell (1979) list a number of common plausiblealternative explanations (or, threats to internal validity). For example, it may be that somehistorical event which occurs at the same time that the program or treatment is instituted wasresponsible for the change in the outcome measures; or, changes in record keeping or measurement systems which occur at the same time as the program might be falsely attributed to

the program. The reader is referred to standard research methods texts for more detaileddiscussions of threats to validity.

This paper is primarily heuristic in purpose. Standard social science methodology textbooks(Cook and Campbell 1979; Judd and Kenny, 1981) typically present an array of research designsand the alternative explanations, which these designs rule out or minimize. This tends to foster a"cookbook" approach to research design - an emphasis on the selection of an available designrather than on the construction of an appropriate research strategy. While standard designs maysometimes fit real-life situations, it will often be necessary to "tailor" a research design tominimize specific threats to validity. Furthermore, even if standard textbook designs are used, an

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conditions. Here, it might be possible to construct a measure of economic conditions andinclude that measure as a covariate in the statistical analysis. One must be careful whenusing covariance adjustments of this type -- "perfect" covariates do not exist in mostsocial research and the use of imperfect covariates will not completely adjust for potentialalternative explanations. Nevertheless causal assertions are likely to be strengthened bydemonstrating that treatment effects occur even after adjusting on a number of goodcovariates.

5. By Preventive Action. When potential threats are anticipated some type of preventiveaction can often rule them out. For example, if the program is a desirable one, it is likelythat the comparison group would feel jealous or demoralized. Several actions can betaken to minimize the effects of these attitudes including offering the program to thecomparison group upon completion of the study or using program and comparisongroups which have little opportunity for contact and communication. In addition, auditingmethods and quality control can be used to track potential experimental dropouts or toinsure the standardization of measurement.

The five categories listed above should not be considered mutually exclusive. The inclusion of measurements designed to minimize threats to validity will obviously be related to the design

structure and is likely to be a factor in the analysis. A good research plan should, where possible.make use of multiple methods for reducing threats. In general, reducing a particular threat bydesign or preventive action will probably be stronger than by using one of the other threeapproaches. The choice of which strategy to use for any particular threat is complex and dependsat least on the cost of the strategy and on the potential seriousness of the threat.

Design Construction

Basic Design Elements. Most research designs can be constructed from four basic elements:

1. Time. A causal relationship, by its very nature, implies that some time has elapsedbetween the occurrence of the cause and the consequent effect. While for somephenomena the elapsed time might be measured in microseconds and therefore might beunnoticeable to a casual observer, we normally assume that the cause and effect insocial science arenas do not occur simultaneously, In design notation we indicate thistemporal element horizontally - whatever symbol is used to indicate the presumed causewould be placed to the left of the symbol indicating measurement of the effect. Thus, aswe read from left to right in design notation we are reading across time. Complex designsmight involve a lengthy sequence of observations and programs or treatments acrosstime. 

2. Program(s) or Treatment(s). The presumed cause may be a program or treatmentunder the explicit control of the researcher or the occurrence of some natural event or program not explicitly controlled. In design notation we usually depict a presumed causewith the symbol "X". When multiple programs or treatments are being studied using thesame design, we can keep the programs distinct by using subscripts such as "X1" or "X2".For a comparison group (i.e., one which does not receive the program under study) no"X" is used. 

3. Observation(s) or Measure(s). Measurements are typically depicted in design notationwith the symbol "O". If the same measurement or observation is taken at every point intime in a design, then this "O" will be sufficient. Similarly, if the same set of measures isgiven at every point in time in this study, the "O" can be used to depict the entire set of measures. However, if different measures are given at different times it is useful tosubscript the "O" to indicate which measurement is being given at which point in time. 

4. Groups or Individuals. The final design element consists of the intact groups or theindividuals who participate in various conditions. Typically, there will be one or more

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program and comparison groups. In design notation, each group is indicated on aseparate line. Furthermore, the manner in which groups are assigned to the conditionscan be indicated by an appropriate symbol at the beginning of each line. Here, "R" willrepresent a group, which was randomly assigned, "N" will depict a group, which wasnonrandom assigned (i.e., a nonequivalent group or cohort) and a "C" will indicate thatthe group was assigned using a cutoff score on a measurement.

Q 4. How is the Case Study method useful in Business Research? Give two specificexamples of how the case study method can be applied to business research.

Ans.: While case study writing may seem easy at first glance, developing an effective case study(also called a success story) is an art. Like other marketing communication skills, learning how towrite a case study takes time. What’s more, writing case studies without careful planning usuallyresults in sub optimal results?Savvy case study writers increase their chances of success by following these ten proventechniques for writing an effective case study:

Involve thecustomer 

throughout theprocess. Involving the customer throughout the case study development process helps ensurecustomer cooperation and approval, and results in an improved case study. Obtain customer permission before writing the document, solicit input during the development, and secureapproval after drafting the document.

• Write all customer quotes for their review. Rather than asking the customer to drafttheir quotes, writing them for their review usually results in more compelling material.

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Case Study Writing Ideas

• Establish a document template. A template serves as a roadmap for the case studyprocess, and ensures that the document looks, feels, and reads consistently. Visually, thetemplate helps build the brand; procedurally, it simplifies the actual writing. Beforebeginning work, define 3-5 specific elements to include in every case study, formalize

those elements, and stick to them.• Start with a bang. Use action verbs and emphasize benefits in the case study title and

subtitle. Include a short (less than 20-word) customer quote in larger text. Then,summarize the key points of the case study in 2-3 succinct bullet points. The goal shouldbe to tease the reader into wanting to read more.

• Organize according to problem, solution, and benefits. Regardless of length, thetime-tested, most effective organization for a case study follows the problem-solution-benefits flow. First, describe the business and/or technical problem or issue; next,describe the solution to this problem or resolution of this issue; finally, describe how thecustomer benefited from the particular solution (more on this below). This natural story-telling sequence resonates with readers.

• Use the general-to-specific-to-general approach. In the problem section, begin with ageneral discussion of the issue that faces the relevant industry. Then, describe the

specific problem or issue that the customer faced. In the solution section, use theopposite sequence. First, describe how the solution solved this specific problem; thenindicate how it can also help resolve this issue more broadly within the industry.Beginning more generally draws the reader into the story; offering a specific exampledemonstrates, in a concrete way, how the solution resolves a commonly faced issue; andconcluding more generally allows the reader to understand how the solution can alsoaddress their problem.

• Quantify benefits when possible. No single element in a case study is more compellingthan the ability to tie quantitative benefits to the solution. For example, “Using Solution Xsaved Customer Y over $ZZZ, ZZZ after just 6 months of implementation;” or, “Thanks toSolution X, employees at Customer Y have realized a ZZ% increase in productivity asmeasured by standard performance indicators.” Quantifying benefits can be challenging,but not impossible. The key is to present imaginative ideas to the customer for ways to

quantify the benefits, and remain flexible during this discussion. If benefits cannot bequantified, attempt to develop a range of qualitative benefits; the latter can be quitecompelling to readers as well.

• Use photos. Ask the customer if they can provide shots of personnel, ideally using thesolution. The shots need not be professionally done; in fact, “homegrown” digital photossometimes lead to surprisingly good results and often appear more genuine. Photosfurther personalize the story and help form a connection to readers.

• Reward the customer. After receiving final customer approval and finalizing the casestudy, provide a pdf, as well as printed copies, to the customer. Another idea is to framea copy of the completed case study and present it to the customer in appreciation for their efforts and cooperation.

Writing a case study is not easy. Even with the best plan, a case study is doomed to failure if thewriter lacks the exceptional writing skills, technical savvy, and marketing experience that these

documents require. In many cases, a talented writer can mean the difference between anineffective case study and one that provides the greatest benefit. If a qualified internal writer isunavailable, consider outsourcing the task to professionals who specialize in case study writing.

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Q 5. What are the differences between observation and interviewing as methods of datacollection? Give two specific examples of situations where either observation or interviewing would be more appropriate.

Ans.: Observation means viewing or seeing. Observation may be defined as a systematicviewing of a specific phenomenon on its proper setting for the specific purpose of gathering datafor a particular study. Observation is classical method of scientific study.

The prerequisites of observation consist of:• Observations must be done under conditions, which will permit accurate results. The

observer must be in vantage point to see clearly the objects to be observed. The

distance and the light must be satisfactory. The mechanical devices used must be in

good working conditions and operated by skilled persons.

• Observation must cover a sufficient number of representative samples of the cases.

• Recording should be accurate and complete.

• The accuracy and completeness of recorded results must be checked. A certain number 

of cases can be observered again by another observer/another set of mechanicaldevices as the case may be. If it is feasible two separate observers and set of 

instruments may be used in all or some of the original observations. The results could

then be compared to determine their accuracy and completeness.

Advantages of observationo The main virtue of observation is its directness it makes it possible to study

behavior as it occurs. The researcher needs to ask people about their behavior 

and interactions he can simply watch what they do and say.

o Data collected by observation may describe the observed phenomena as they

occur in their natural settings. Other methods introduce elements or artificiality

into the researched situation for instance in interview the respondent may notbehave in a natural way. There is no such artificiality in observational studies

especially when the observed persons are not aware of their being observed.

o Observations in more suitable for studying subjects who are unable to articulate

meaningfully e.g. studies of children, tribal animals, birds etc.

o Observations improve the opportunities for analyzing the contextual back ground

of behavior. Furthermore verbal resorts can be validated and compared with

behavior through observation. The validity of what men of position and authority

say can be verified by observing what they actually do.

o Observations make it possible to capture the whole event as it occurs. For example only observation can be providing an insight into all the aspects of the

process of negotiation between union and management representatives.

o Observation is less demanding of the subjects and has less biasing effect on

their conduct than questioning.

o It is easier to conduct disguised observation studies than disguised questioning.

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o Mechanical devices may be used for recording data in order to secure more

accurate data and also of making continuous observations over longer periods.

Interviews are a crucial part of the recruitment process for all Organisations. Their purpose is togive the interviewer(s) a chance to assess your suitability for the role and for you to demonstrateyour abilities and personality. As this is a two-way process, it is also a good opportunity for you to

ask questions and to make sure the organisation and position are right for you.Interview format 

Interviews take many different forms. It is a good idea to ask the organisation in advance whatformat the interview will take.

• Competency/criteria based interviews - These are structured to reflect thecompetencies or qualities that an employer is seeking for a particular job, which willusually have been detailed in the job specification or advert. The interviewer is looking for evidence of your skills and may ask such things as: ‘Give an example of a time youworked as part of a team to achieve a common goal.’

The organisation determines the selection criteria based on the roles they are recruiting for and then, in an interview, examines whether or not you have evidence of possessing 

these.Recruitment Manager, The Cooperative Group

• Technical interviews - If you have applied for a job or course that requires technicalknowledge, it is likely that you will be asked technical questions or has a separatetechnical interview. Questions may focus on your final year project or on real or hypothetical technical problems. You should be prepared to prove yourself, but also toadmit to what you do not know and stress that you are keen to learn. Do not worry if youdo not know the exact answer - interviewers are interested in your thought process andlogic.

• Academic interviews - These are used for further study or research positions.Questions are likely to center on your academic history to date.

• Structured interviews - The interviewer has a set list of questions, and asks all thecandidates the same questions.

• Formal/informal interviews - Some interviews may be very formal, while others will feelmore like an informal chat about you and your interests. Be aware that you are still beingassessed, however informal the discussion may seem.

• Portfolio based interviews - If the role is within the arts, media or communicationsindustries, you may be asked to bring a portfolio of your work to the interview, and tohave an in-depth discussion about the pieces you have chosen to include.

• Senior/case study interviews - These ranges from straightforward scenario questions(e.g. ‘What would you do in a situation where…?’) to the detailed analysis of ahypothetical business problem. You will be evaluated on your analysis of the problem,how you identify the key issues, how you pursue a particular line of thinking and whether you can develop and present an appropriate framework for organising your thoughts.

Specific types of interview 

The Screening Interview

Companies use screening tools to ensure that candidates meet minimum qualificationrequirements. Computer programs are among the tools used to weed out unqualified candidates.(This is why you need a digital resume that is screening-friendly. See our resume center for help.)Sometimes human professionals are the gatekeepers. Screening interviewers often have honedskills to determine whether there is anything that might disqualify you for the position. Remember-they does not need to know whether you are the best fit for the position, only whether you are not

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a match. For this reason, screeners tend to dig for dirt. Screeners will hone in on gaps in your employment history or pieces of information that look inconsistent. They also will want to knowfrom the outset whether you will be too expensive for the company.

Some tips for maintaining confidence during screening interviews:

• Highlight your accomplishments and qualifications.• Get into the straightforward groove. Personality is not as important to the screener as

verifying your qualifications. Answer questions directly and succinctly. Save your winningpersonality for the person making hiring decisions!

• Be tactful about addressing income requirements. Give a range, and try to avoid givingspecifics by replying, "I would be willing to consider your best offer."

• If the interview is conducted by phone, it is helpful to have note cards with your vitalinformation sitting next to the phone. That way, whether the interviewer catches yousleeping or vacuuming the floor, you will be able to switch gears quickly.

The Informational Interview

On the opposite end of the stress spectrum from screening interviews is the informationalinterview. A meeting that you initiate, the informational interview is underutilized by job-seekerswho might otherwise consider themselves savvy to the merits of networking. Job seekersostensibly secure informational meetings in order to seek the advice of someone in their currentor desired field as well as to gain further references to people who can lend insight. Employersthat like to stay apprised of available talent even when they do not have current job openings, areoften open to informational interviews, especially if they like to share their knowledge, feelflattered by your interest, or esteem the mutual friend that connected you to them. During aninformational interview, the jobseeker and employer exchange information and get to know oneanother better without reference to a specific job opening.

This takes off some of the performance pressure, but be intentional nonetheless:

• Come prepared with thoughtful questions about the field and the company.• Gain references to other people and make sure that the interviewer would be comfortable

if you contact other people and use his or her name.• Give the interviewer your card, contact information and resume.• Write a thank you note to the interviewer.

The Directive Style

In this style of interview, the interviewer has a clear agenda that he or she follows unflinchingly.Sometimes companies use this rigid format to ensure parity between interviews; wheninterviewers ask each candidate the same series of questions, they can more readily compare theresults. Directive interviewers rely upon their own questions and methods to tease from you whatthey wish to know. You might feel like you are being steam-rolled, or you might find the

conversation develops naturally. Their style does not necessarily mean that they have dominanceissues, although you should keep an eye open for these if the interviewer would be your supervisor.

Either way, remember:

• Flex with the interviewer, following his or her lead.

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• Do not relinquish complete control of the interview. If the interviewer does not ask you for information that you think is important to proving your superiority as a candidate, politelyinterject it.

The Meandering Style

This interview type, usually used by inexperienced interviewers, relies on you to lead thediscussion. It might begin with a statement like "tell me about yourself," which you can use to your advantage. The interviewer might ask you another broad, open-ended question before falling intosilence. This interview style allows you tactfully to guide the discussion in a way that best servesyou.

The following strategies, which are helpful for any interview, are particularly important wheninterviewers use a non-directive approach:

• Come to the interview prepared with highlights and anecdotes of your skills, qualities andexperiences. Do not rely on the interviewer to spark your memory-jot down some notesthat you can reference throughout the interview.

• Remain alert to the interviewer. Even if you feel like you can take the driver's seat and go

in any direction you wish, remain respectful of the interviewer's role. If he or she becomesmore directive during the interview, adjust.

• Ask well-placed questions. Although the open format allows you significantly to shape theinterview, running with your own agenda and dominating the conversation means thatyou run the risk of missing important information about the company and its needs.

Q 6. Case Study: You are engaged to carry out a market survey on behalf of a leadingNewspaper that is keen to increase its circulation in Bangalore City, in order to ascertainreader habits and interests. What type of research report would be most appropriate?Develop an outline of the research report with the main sections.

Ans.: There are four major interlinking processes in the presentation of a literature review:

1. Critiquing rather than merely listing each item a good literature review is led by your owncritical thought processes - it is not simply a catalogue of what has been written.

Once you have established which authors and ideas are linked, take each group in turnand really think about what you want to achieve in presenting them this way. This is your opportunity for showing that you did not take all your reading at face value, but that youhave the knowledge and skills to interpret the authors' meanings and intentions in relationto each other, particularly if there are conflicting views or incompatible findings in aparticular area.

Rest assured that developing a sense of critical judgment in the literature surrounding atopic is a gradual process of gaining familiarity with the concepts, language, terminology

and conventions in the field. In the early stages of your research you cannot be expectedto have a fully developed appreciation of the implications of all findings.

As you get used to reading at this level of intensity within your field you will find it easier and more purposeful to ask questions as you read:

o What is this all about?o Who is saying it and what authorities do they have?o Why is it significant?

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o What is its context?o How was it reached?o How valid is it?o How reliable is the evidence?o What has been gained?o What do other authors say?

o How does it contribute?o So what?

2. Structuring the fragments into a coherent body through your reading and discussionswith your supervisor during the searching and organising phases of the cycle, you willeventually reach a final decision as to your own topic and research design.

As you begin to group together the items you read, the direction of your literature reviewwill emerge with greater clarity. This is a good time to finalise your concept map, groupinglinked items, ideas and authors into firm categories as they relate more obviously to your own study.

Now you can plan the structure of your written literature review, with your own intentionsand conceptual framework in mind. Knowing what you want to convey will help youdecide the most appropriate structure.

A review can take many forms; for example:

o An historical survey of theory and research in your fieldo A synthesis of several paradigmso A process of narrowing down to your own topic

It is likely that your literature review will contain elements of all of these.

As with all academic writing, a literature review needs:

o An introductiono A bodyo A conclusion

The introduction sets the scene and lays out the various elements that are to beexplored.

The body takes each element in turn, usually as a series of headed sections andsubsections. The first paragraph or two of each section mentions the major authors inassociation with their main ideas and areas of debate. The section then expands onthese ideas and authors, showing how each relates to the others, and how the debateinforms your understanding of the topic. A short conclusion at the end of each section

presents a synthesis of these linked ideas.

The final conclusion of the literature review ties together the main points from each of your sections and this is then used to build the framework for your own study. Later,when you come to write the discussion chapter of your thesis, you should be able torelate your findings in one-to-one correspondence with many of the concepts or questions that were firmed up in the conclusion of your literature review.

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3. Controlling the 'voice' of your citations in the text (by selective use of direct quoting,paraphrasing and summarizing)

You can treat published literature like any other data, but the difference is that it is notdata you generated yourself.

When you report on your own findings, you are likely to present the results with referenceto their source, for example:

o 'Table 2 shows that sixteen of the twenty subjects responded positively.'

When using published data, you would say:

o 'Positive responses were recorded for 80 per cent of the subjects (see table 2).'o 'From the results shown in table 2, it appears that the majority of subjects

responded positively.'

In these examples your source of information is table 2. Had you found the same results

on page 17 of a text by Smith published in 1988, you would naturally substitute the name,date and page number for 'table 2'. In each case it would be your voice introducing a factor statement that had been generated somewhere else.

You could see this process as building a wall: you select and place the 'bricks' and your 'voice' provides the ‘mortar’, which determines how strong the wall will be. In turn, this issignificant in the assessment of the merit and rigor of your work.

There are three ways to combine an idea and its source with your own voice:

o Direct quoteo Paraphraseo Summary

In each method, the author's name and publication details must be associated with thewords in the text, using an approved referencing system. If you don't do this you would bein severe breach of academic convention, and might be penalized. Your field of study hasits own referencing conventions you should investigate before writing up your results.

Direct quoting repeats exact wording and thus directly represents the author:

o 'Rain is likely when the sky becomes overcast' (Smith 1988, page 27).

If the quotation is run in with your text, single quotation marks are used to enclose it, andit must be an identical copy of the original in every respect.

Overuse or simple 'listing' of quotes can substantially weaken your own argument bysilencing your critical view or voice.

Paraphrasing is repeating an idea in your own words, with no loss of the author'sintended meaning:

o As Smith (1988) pointed out in the late eighties, rain may well be indicated by thepresence of cloud in the sky.

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Paraphrasing allows you to organize the ideas expressed by the authors without beingrigidly constrained by the grammar, tense and vocabulary of the original. You retain adegree of flexibility as to whose voice comes through most strongly.

Summarizing means to shorten or crystallize a detailed piece of writing by restating themain points in your own words and in the order in which you found them. The original

writing is 'described' as if from the outside, and it is your own voice that is predominant:

o Referring to the possible effects of cloudy weather, Smith (1988) predicted thelikelihood of rain.

o Smith (1988) claims that some degree of precipitation could be expected as theresult of clouds in the sky: he has clearly discounted the findings of Jones (1986).

4. Using appropriate language

Your writing style represents you as a researcher, and reflects how you are dealing withthe subtleties and complexities inherent in the literature.

Once you have established a good structure with appropriate headings for your literaturereview, and once you are confident in controlling the voice in your citations, you shouldfind that your writing becomes more lucid and fluent because you know what you want to

say and how to say it.

The good use of language depends on the quality of the thinking behind the writing, andon the context of the writing. You need to conform to discipline-specific requirements.However, there may still be some points of grammar and vocabulary you would like toimprove. If you have doubts about your confidence to use the English language well, youcan help yourself in several ways:

o Ask for feedback on your writing from friends, colleagues and academicso Look for specific language information in reference materialso Access programs or self-paced learning resources which may be available on

your campus

Grammar tips - practical and helpful The following guidance on tenses and other language tips may be useful.

Which tense should I use?

Use present tense:

o For generalizations and claims:

The sky is blue.o To convey ideas, especially theories, which exist for the reader at the time of 

reading: I think therefore I am.

o For authors' statements of a theoretical nature, which can then be compared onequal terms with others:

Smith (1988) suggests that...o In referring to components of your own document:

Table 2 shows...

Use present perfect tense for:

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o Recent events or actions that are still linked in an unresolved way to the present:

Several studies have attempted to...

Use simple past tense for:

o Completed events or actions:

Smith (1988) discovered that...

Use past perfect tense for:

o Events which occurred before a specified past time:

Prior to these findings, it had been thought that...

Use modals (may, might, could, would, should) to:

o Convey degrees of doubt

This may indicate that ... this would imply that...

Other language tips

o Convey your meaning in the simplest possible way. Don't try to use anintellectual tone for the sake of it, and do not rely on your reader to read your mind!

o Keep sentences short and simple when you wish to emphasise a point.o Use compound (joined simple) sentences to write about two or more ideas which

may be linked with 'and', 'but', 'because', 'whereas' etc.o Use complex sentences when you are dealing with embedded ideas or those that

show the interaction of two or more complex elements.o Verbs are more dynamic than nouns, and nouns carry information more densely

than verbs.o

Select active or passive verbs according to whether you are highlighting the'doer' or the 'done to' of the action.o Keep punctuation to a minimum. Use it to separate the elements of complex

sentences in order to keep subject, verb and object in clear view.o Avoid densely packed strings of words, particularly nouns.

The total process

The story of a research study 

IntroductionI looked at the situation and found that I had a question to ask about it. I wanted to investigatesomething in particular.

Review of literatureSo I read everything I could find on the topic - what was already known and said and what hadpreviously been found. I established exactly where my investigation would fit into the big picture,and began to realise at this stage how my study would be different from anything done previously.

MethodologyI decided on the number and description of my subjects, and with my research question clearly inmind, designed my own investigation process, using certain known research methods (and

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perhaps some that are not so common). I began with the broad decision about which researchparadigm I would work within (that is, qualitative/quantitative, critical/interpretive/ empiricist). ThenI devised my research instrument to get the best out of what I was investigating. I knew I wouldhave to analyse the raw data, so I made sure that the instrument and my proposed method(s) of analysis were compatible right from the start. Then I carried out the research study and recordedall the data in a methodical way according to my intended methods of analysis. As part of theanalysis, I reduced the data (by means of my preferred form of classification) to manageablethematic representation (tables, graphs, categories, etc). It was then that I began to realise what Ihad found.

Findings/resultsWhat had I found? What did the tables/graphs/categories etc. have to say that could be pinneddown? It was easy enough for me to see the salient points at a glance from these records, but inwriting my report, I also spelled out what I had found truly significant to make sure my readers didnot miss it. For each display of results, I wrote a corresponding summary of importantobservations relating only elements within my own set of results and comparing only like with like.I was careful not to let my own interpretations intrude or voice my excitement just yet. I wanted tostate the facts - just the facts. I dealt correctly with all inferential statistical procedures, applyingtests of significance where appropriate to ensure both reliability and validity. I knew that I wantedmy results to be as watertight and squeaky clean as possible. They would carry a great deal morecredibility, strength and thereby academic 'clout' if I took no shortcuts and remained both rigorousand scholarly.

DiscussionNow I was free to let the world know the significance of my findings. What did I find in the resultsthat answered my original research question? Why was I so sure I had some answers? Whatabout the unexplained or unexpected findings? Had I interpreted the results correctly? Couldthere have been any other factors involved? Were my findings supported or contested by theresults of similar studies? Where did that leave mine in terms of contribution to my field? Can Iactually generalise from my findings in a breakthrough of some kind, or do I simply see myself asreinforcing existing knowledge? And so what, after all? There were some obvious limitations tomy study, which, even so, I'll defend to the hilt. But I won't become over-apologetic about thethings left undone, or the abandoned analyses, the fascinating byways sadly left behind. I havemy memories...

ConclusionWe'll take a long hard look at this study from a broad perspective. How does it rate? How did Iend up answering the question I first thought of? The conclusion needs to be a few clear, succinctsentences. That way, I'll know that I know what I'm talking about. I'll wrap up with whatever generalizations I can make, and whatever implications have arisen in my mind as a result of doing this thing at all. The more you find out, the more questions arise. How I wonder what youare ... how I speculate. OK, so where do we all go from here?

Three stages of research

1. Reading2. Research design and implementation

3. Writing up the research report or thesis

Use an active, cyclical writing process: draft, check, reflect, revise, redraft.

Establishing good practice

1. Keep your research question always in mind.

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2. Read widely to establish a context for your research.3. Read widely to collect information, which may relate to your topic, particularly to your 

hypothesis or research question.4. Be systematic with your reading, note-taking and referencing records.5. Train yourself to select what you do need and reject what you don't need.6. Keep a research journal to reflect on your processes, decisions, state of mind, changes

of mind, reactions to experimental outcomes etc.7. Discuss your ideas with your supervisor and interested others.8. Keep a systematic log of technical records of your experimental and other research data,

remembering to date each entry, and noting any discrepancies or unexpectedoccurrences at the time you notice them.

9. Design your research approaches in detail in the early stages so that you haveframeworks to fit findings into straightaway.

10. Know how you will analyse data so that your formats correspond from the start.11. Keep going back to the whole picture. Be thoughtful and think ahead about the way you

will consider and store new information as it comes to light.

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