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Fall /August 2012, MBA-3rd Semester

MB0050: Research Methodology Roll No. : 541110058 Page 1

Master of Business Administration (MBA)

Semester

3

MB0050Research Methodology

(4 Credits)

(Book ID: B1206)

Assignment Set- 2


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1. Define Research. What are the features and types of Research?

Research simply means a search of facts answers to questions and solutions to

problems. It is a purposive investigation. It is an organized inquiry. It seeks to find

explanations to unexplained phenomenon to clarify the doubtful facts and to correct the

misconceived facts.

Although any typology of research is inevitably arbitrary, research may be classified

crudely according to its major intent or the methods. According to the intent, research

may be classified as:

Features

1. It is a systematic and critical investigation into a phenomenon.

2. It is a purposive investigation aiming at describing, interpreting and explaining a

phenomenon.

3. It adopts scientific method.

4. It is objective and logical, applying possible test to validate the measuring tools

and the conclusions reached.

5. It is based upon observable experience or empirical evidence.

6. Research is directed towards finding answers to pertinent questions and solutions

to problems.

7. It emphasizes the development of generalization, principles or theories.

8. The purpose of research is not only to arrive at an answer but also to stand up the

test of criticism.

Types of Research - Although any typology of research is inevitably arbitrary, Research

may be classified crudely according to its major intent or the methods. According to theintent, research may be classified as:


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Pure Research - It is undertaken for the sake of knowledge without any intention to

apply it in practice, e.g., Einsteins theory of relativity, Newtons contributions, Galileos

contribution, etc. It is also known as basic or fundamental research. It is undertaken

out of intellectual curiosity or inquisitiveness. It is not necessarily problem-oriented. It

aims at extension of knowledge. It may lead to either discovery of a new theory or

refinement of an existing theory. It lays foundation for applied research. It offers

solutions to many practical problems. It helps to find the critical factors in a practical

problem. It develops many alternative solutions and thus enables us to choose the best

solution.

Applied Research - It is carried on to find solution to a real-life problem requiring anaction or policy decision. It is thus problem-oriented and action-directed. It seeks an

immediate and practical result, e.g., marketing research carried on for developing a

new market or for studying the post-purchase experience of customers. Though the

immediate purpose of an applied research is to find solutions to a practical problem, it

may incidentally contribute to the development of theoretical knowledge by leading to

the discovery of new facts or testing of theory or o conceptual clarity. It can put theory

to the test. It may aid in conceptual clarification. It may integrate previously existing

theories.

Research - It is also known as formulative research. It is preliminary study of an

unfamiliar problem about which the researcher has little or no knowledge. It is ill-

structured and much less focused on pre-determined objectives. It usually takes the

form of a pilot study. The purpose of this research may be to generate new ideas, or to

increase the researchers familiarity with the problem or to make a precise formulation

of the problem or to gather information for clarifying concepts or to determine whether

it is feasible to attempt the study. Katz conceptualizes two levels of exploratory studies.

At the first level is the discovery of the significant variable in the situations; at the

second, the discovery of relationships between variables.


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Descriptive Study - It is a fact-finding investigation with adequate interpretation. It is

the simplest type of research. It is more specific than an exploratory research. It aims at

identifying the various characteristics of a community or institution or problem under

study and also aims at a classification of the range of elements comprising the subject

matter of study. It contributes to the development of a young science and useful in

verifying focal concepts through empirical observation. It can highlight important

methodological aspects of data collection and interpretation. The information obtained

may be useful for prediction about areas of social life outside the boundaries of the

research. They are valuable in providing facts needed for planning social action

program.

Diagnostic Study - It is similar to descriptive study but with a different focus. It is

directed towards discovering what is happening, why it is happening and what can be

done about. It aims at identifying the causes of a problem and the possible solutions for

it. It may also be concerned with discovering and testing whether certain variables are

associated. This type of research requires prior knowledge of the problem, its thorough

formulation, clear-cut definition of the given population, adequate methods for

collecting accurate information, precise measurement of variables, statistical analysis

and test of significance.

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 developmental projects on the development of the project area. It is thus

directed to assess or appraise the quality and quantity of an activity and its

performance, and to specify its attributes and conditions required for its success. It is

concerned with causal relationships and is more actively guided by hypothesis. It is

concerned also with change over time.


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Action Research - It is a type of evaluation study. It is a concurrent evaluation study of

an action programme launched for solving a problem for improving an exiting situation.

It includes six major steps: diagnosis, sharing of diagnostic information, planning,

developing change programme, initiation of organizational change, implementation of

participation and communication process, and post experimental evaluation.

According to methods of study, research may be classified as:

Experimental Research - Market research conducted by experiencing the outcome

achieved through the use of a good or service. The outcome may be experienced by

a sample group or those conducting the research.

Analytical StudyIt is a system of procedures and techniques of analysis applied to

quantitative data. It may consist of a system of mathematical models or statistical

techniques, applicable to numerical data. Hence it is also known as the statistical

method.

Survey Research - A method of sociological investigation that uses question based or

statistical surveys to collect information about how people think and act. For example, a

possible application of survey research to a business context might involve looking at

how effective mass media is in helping form and shift public opinion.
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2. How is a research problem formulated? What are the sources from which one may

be able to identify research problems?

The selection of one appropriate researchable problem out of the identified problems

requires evaluation of those alternatives against certain criteria, which may be grouped

into:

A. Internal Source -

1. Researchers interest: - The problem should interest the researcher and be a

challenge to him. Without interest and curiosity, he may not develop sustained

perseverance. Even a small difficulty may become an excuse for discontinuing the

study. Interest in a problem depends upon the researchers educationalbackground, experience, outlook and sensitivity.

2. Researchers competence: - A mere interest in a problem will not do. The

researcher must be competent to plan and carry out a study of the problem. He

must have the ability to grasp and deal with int. he must possess adequate

knowledge of the subject-matter, relevant methodology and statistical

procedures.

3. Researchers own resource: - In the case of a research to be done by a researcher

on his won, consideration of his own financial resource is pertinent. If it is beyond

his means, he will not be able to complete the work, unless he gets someexternal financial support. Time resource is more important than finance.

Research is a time-consuming process; hence it should be properly utilized.

B. External Source

1. Research-ability of the problem:- The problem should be researchable, i.e.,amendable for finding answers to the questions involved in it through scientific

method. To be researchable a question must be one for which observation or

other data collection in the real world can provide the answer.

2. Importance and urgency:-Problems requiring investigation are unlimited, but

available research efforts are very much limited. Therefore, in selecting problems

for research, their relative importance and significance should be considered. An

important and urgent problem should be given priority over an unimportant one.


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3. Novelty of the problem:-The problem must have novelty. There is no use of wasting

ones time and energy on a problem already studied thoroughly by others. This

does not mean that replication is always needless. In social sciences in some

cases, it is appropriate to replicate (repeat) a study in order to verify the validity

of its findings to a different situation.

4. Feasibility:-A problem may be a new one and also important, but if research on it

is not feasible, it cannot be selected. Hence feasibility is a very important

consideration

5. Facilities:- Research requires certain facilities such as well-equipped library

facility, suitable and competent guidance, data analysis facility, etc. Hence the

availability of the facilities relevant to the problem must be considered.

6. Usefulness and social relevance:-Above all, the study of the problem should

make significant contribution to the concerned body of knowledge or to thesolution of some significant practical problem. It should be socially relevant. This

consideration is particularly important in the case of higher level academic

research and sponsored research.

7. Research personnel:- Research undertaken by professors and by research

organizations require the services of investigators and research officers. But in

India and other developing countries, research has not yet become a prospective

profession. Hence talent persons are not attracted to research projects.

Each identified problem must be evaluated in terms of the above internal and external

criteria and the most appropriate one may be selected by a research scholar.

The sources from which one may be able to identify research problems or develop

problems awareness are:

Review of literature

Academic experience

Daily experience

Exposure to field situations

Consultations

Brain storming Research

Intuition


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The problem selected for research may initially be a vague topic. The question to be

studied or the problem to be solved may not be known. Hence the selected problem

should be defined and formulated. This is a difficult process. It requires intensive

reading of a few selected articles or chapters in books in order to understand the nature

of the problem selected. The process of defining a problem includes:

Developing title - The title should be carefully worded. It should indicate the core of the

study, reflect the real intention of the researcher, and show on what is the focus e.g.,

Financing small-scale industries by commercial banks. This shows that the focus is on

commercial banks and not on small-scale industries. On the other hand, if the title is

The Financial Problem of Small-scale industries, the focus is on small-scale industries.

Building a conceptual model - On the basis of our theoretical knowledge of the

phenomenon under study, the nature of the phenomenon, its properties /elements and

their inter-relations should be identified and structured into framework. This conceptual

model gives an exact idea of the research problem and shows its various properties and

variables to be studied. It serves as a basis for the formulation of the objectives of the

study, on the hypothesis to be tested. In order to work out a conceptual model we must

make a careful and critical study of the available literature on the subject-matter of the

selected research problem. It is for this reason; a researcher is expected to select a

problem for research in his field of specialization. Without adequate background

knowledge, a researcher cannot grasp and comprehend the nature of the research

problem.


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Define the Objective of the Study - The objectives refer to the questions to be answered

through the study. They indicate what we are trying to get through the study. The

objectives are derived from the conceptual model. They state which elements in the

conceptual model-which levels of, which kinds of cases, which properties, and which

connections among properties are to be investigated, but it is the conceptual model

that defines, describes, and states the assumptions underlying these elements. The

objectives may aim at description or explanation or analysis of causal relationship

between variables, and indicate the expected results or outcome of the study. The

objectives may be specified in the form of either the statements or the questions

Formulating the research problem and hypothesis acts as a major step or phase in the

research methodology. In research, the foremost step that comes into play is that of

defining the research problem and it becomes almost a necessity to have the basic

knowledge and understanding of most of its elements as this would help a lot in making

a correct decision. The research problem can be said to be complete only if it is able to

specify about the unit of analysis, time and space boundaries, features that are under

study, specific environmental conditions that are present in addition to prerequisite of

the research process.


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3. What are the types of Observations? What is the utility of Observation in Business

Research?

Observations may be classified in different ways. With reference to investigators role, it

may be classified into (a) participant observation and (b) non-participant observation. In

terms of mode of observation, it may be classified into (c) direct observation. With

reference to the rigor of the system adopted. Observation is classified into (e) controlled

observation, and (f) uncontrolled observation.

Participant Observation - In this observation, the observer is a part of the phenomenon

or group which is observed and he acts as both an observer and a participant. For

example, a study of tribal customs by an anthropologist by taking part in tribal activities

like folk dance. The persons who are observed should not be aware of the researchers

purpose. Then only their behavior will be natural. The concealment of research

objective and researchers identity is justified on the ground that it makes it possible to

study certain aspects of the groups culture which are not revealed to outsiders.

Advantages:

The advantages of participant observation are:

1. The observer can understand the emotional reactions of the observed group, and

get a deeper insight of their experiences.2. The observer will be able to record context which gives meaning to the observed

behavior and heard statements.

Disadvantages:

Participant observation suffers from some demerits.

1. The participant observer narrows his range of observation. For example, if there

is a hierarchy of power in the group/community under study, he comes to occupy

one position within in, and thus other avenues of information are closed to him.

2. To the extent that the participant observer participates emotionally, theobjectivity is lost.

3. Another limitation of this method is the dual demand made on the observer.

Recording can interfere with participation, and participation can interfere with


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4. observation. Recording on the spot is not possible and it has to be postponed

until the observer is alone. Such time lag results in some inaccuracy in recording

Non-participant observations -In this method, the observer stands apart and does not

participate in the phenomenon observed. Naturally, there is no emotional involvement

on the part of the observer. This method calls for skill in recording observations in an

unnoticed manner.

Direct observation -This means observation of an event personally by the observer

when it takes place. This method is flexible and allows the observer to see and record

subtle aspects of events and behaviour as they occur. He is also free to shift places,

change the focus of the observation. A limitation of this method is that the observe rs

perception circuit may not be able to cover all relevant events when the latter move

quickly, resulting in the incompleteness of the observation.

Indirect observation -This does not involve the physical presence of the observer, and

the recording is done by mechanical, photographic or electronic devices, e.g. recording

customer and employee movements by a special motion picture camera mounted in a

department of a large store. This method is less flexible than direct observations, but it

is less biasing and less erratic in recording accuracy. It is also provides a permanent

record for an analysis of different aspects of the event.

Controlled observation - This involves standardization of observational techniques and

exercises of maximum control over extrinsic and intrinsic variables by adopting

experimental design and systematically recording observations. Controlled observation

is carried out either in the laboratory or in the field. It is typified by clear and explicit

decisions on what, how and when to observe.

Uncontrolled observation

This does not involve control over extrinsic and intrinsic variables. It is primary used for

descriptive research. Participant observation is a typical uncontrolled one .

Observation is suitable for a variety of research purposes. It may be used for studying


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(a) The behaviour of human beings in purchasing goods and services. :-life style,

customs, and manner, interpersonal relations, group dynamics, crowd behaviour,

leadership styles, managerial style, other behaviours and actions;

(b) The behaviour of other living creatures like birds, animals etc.

(c) Physical characteristics of inanimate things like stores, factories, residences etc.

(d) Flow of traffic and parking problems

(e) Movement of materials and products through a plant.

Utilities of observation in business research

Observation is suitable for a variety of research purposes. It may be used for

studying (a) the behavior of human beings in purchasing goods and services, life

style, customs, and manner, interpersonal relations, group dynamics, crowd

behavior, leadership styles, managerial styles, other behaviors and actions;

(b) The behavior of other living creatures like birds, animals etc.

(c) Physical characteristics of inanimate

(d) Flow of traffic and parking problems

(e) Movement of materials and products through a plant.


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4. What is Research Design? What are the different types of Research Designs?

A research design is a logical and systematic plan prepared for directing a research

study. It specifies the objective of the study, the methodology and techniques to be

adopted for achieving the objectives.

Research design plans manage and systematize quantitative or qualitative data

collection. Quantitative research finds the answer to an inquiry by compiling numerical

evidence. It counts and classifies components and creates statistical models to explain

what is observed. Qualitative research is subjective in approach, and attempts to

understand human behavior and the rationales that govern it. It generates mainly verbal

data that is analyzed and interpreted. Under each of these two main categories fall a

variety of research designs suitable to particular studies.

There are number of crucial research choices, various writers advance different

classifications schemes, some of which are:

1. Experimental, historical and inferential designs (American Marketing Association)

2. Exploratory, descriptive and causal designs (Selltiz, Jahoda, Deutsch and Cook).

3. Experimental, and expost fact (Kerlinger)

4. Historical method, and case and clinical studies (Goode and Scates)

5. Sample surveys, field studies, experiments in field settings, and laboratory

experiments (Festiiinger and Katz)

6. Exploratory, descriptive and experimental studies (Body and Westfall)

7. Exploratory, descriptive and casual (Green and Tull)

8. Experimental, quasi-experimental (Nachmias and Nachmias)


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9. True experimental, quasi experimental and non-experimental designs (Smith).

10.Experimental, pre-experimental, quasi-experimental designs and survey research

(Kidder and Judd).

5. Explain the Sampling Process and briefly describe the methods of Sampling.

Decision process of sampling is complicated one. The researcher has to first identify the

limiting factor or factors and must judiciously balance the conflicting factors. The

various criteria governing the choice of the sampling technique:

1. 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 an

appropriate probability sampling method must be selected. The choice of a

particular type of probability sampling depends on the geographical area of the

survey and the size and the nature of the population under study.

2. Measurability: The application of statistical inference theory requirescomputation of the sampling error from the sample itself. Probability samples

only allow such computation. Hence, where the research objective requires

statistical inference, the sample should be drawn by applying simple random

sampling method or stratified random sampling method, depending on whether

the population is homogenous or heterogeneous.

3. Degree of Precision: Should the results of the survey be very precise, or evenrough results could serve the purpose? The desired level of precision as one ofthe criteria of sampling method selection. Where a high degree of precision of

results is desired, probability sampling should be used. Where even crude results

would serve the purpose (E.g., marketing surveys, readership surveys etc) any

convenient non-random sampling like quota sampling would be enough.


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4. Information about Population: How much information is available about thepopulation to be studied? Where no list of population and no information about

its nature are available, it is difficult to apply a probability sampling method. Then

exploratory study with non-probability sampling may be made to gain a better

idea of population. After gaining sufficient knowledge about the population

through the exploratory study, appropriate probability sampling design may be

adopted.

5. 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 a simple random sampling will give a representative sample. If

the population is heterogeneous, stratified random sampling is appropriate.

6. 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.

7. Financial resources: If the available finance is limited, it may become necessaryto choose a less costly sampling plan like multistage cluster sampling or even

quota sampling as a compromise. However, if the objectives of the study and the

desired level of precision cannot be attained within the stipulated budget, there

is no alternative than 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 the research objective and the nature of population.

8. Time Limitation: The time limit within which the research project should becompleted restricts the choice of a sampling method. Then, as a compromise, it

may become necessary to choose less time consuming methods like simple

random sampling instead of stratified sampling/sampling with probability

proportional to size; multi-stage cluster sampling instead of single-stage samplingof elements. Of course, the precision has to be sacrificed to some extent.

9. Economy: It should be another criterion in choosing the sampling method. Itmeans 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.


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The above criteria frequently conflict and the researcher must balance and blend them

to obtain to obtain a good sampling plan. The chosen plan thus represents an

adaptation of the sampling theory to the available facilities and resources. That is, it

represents a compromise between idealism and feasibility. One should use simple

workable methods instead of unduly elaborate and complicated techniques

Sampling techniques or methods may be classified into two generic types:

Probability or Random Sampling

Probability sampling is based on the theory of probability. It is also known as random

sampling. It provides a known nonzero chance of selection for each population element.

It is used when generalization is the objective of study, and a greater degree of accuracyof estimation of population parameters is required. The cost and time required is high

hence the benefit derived from it should justify the costs.

The following are the types of probability sampling:

I. Simple Random Sampling: This sampling technique gives each element an equal

and independent chance of being selected. An equal chance means equal

probability of selection. An independent chance means that the draw of one

element will not affect the chances of other elements being selected. The

procedure of drawing a simple random sample consists of enumeration of all

elements in the population.

a. Preparation of a List of all elements, giving them numbers in serial order 1, 2, B,

and so on, and

b. Drawing sample numbers by using (i) lottery method, (ii) a table of random

numbers or (iii) a computer.

Suitability: This type of sampling is suited for a small homogeneous population.

Advantages: The advantage of this is that it is one of the easiest methods, all theelements in the population have an equal chance of being selected, simple to

understand, does not require prior knowledge of the true composition of the

population.


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Disadvantages: It is often impractical because of non-availability of population list or of

difficulty in enumerating the population, does not ensure proportionate representation

and it may be expensive in time and money. The amount of sampling error associated

with any sample drawn can easily be computed. But it is greater than that in other

probability samples of the same size, because it is less precise than other methods.

II. Stratified Random Sampling: This is an improved type of random or probability

sampling. In this method, the population is sub-divided into homogenous groups

or strata, and from each stratum, random sample is drawn. E.g., university

students may be divided on the basis of discipline, and each discipline group may

again be divided into juniors and seniors. Stratification is necessary for increasing

a samples statistical efficiency, providing adequate data for analyzing the various

sub-populations and applying different methods to different strata. The stratifiedrandom sampling is appropriate for a large heterogeneous population.

Stratification process involves three major decisions. They are stratification base

or bases, number of strata and strata sample sizes.

Stratified random sampling may be classified into:

a) Proportionate stratified sampling: This sampling involves drawing a sample from

each stratum in proportion to the latters share in the total population. It gives

proper representation to each stratum and its statistical efficiency is generally

higher. This method is therefore very popular.

E.g., if the Management Faculty of a University consists of the following

specialization groups:

Specialization

stream

No. of students Proportion of

each stream

Production

Finance

Marketing

Ruraldevelopment

40

20

30

10

0.4

0.2

0.3

0.1

100 1.0


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The research wants to draw an overall sample of 30. Then the strata sample sizes would

be:

Strata Sample size

Production

Finance

Marketing

Rural

development

30 x 0.4

30 x 0.2

30 x 0.3

30 x 0.1

12

6

9

3

30

Advantages: Stratified random sampling enhances the representativeness to eachsample, gives higher statistical efficiency, easy to carry out, and gives a self-weighing

sample.

Disadvantages: A prior knowledge of the composition of the population and the

distribution of the population, it is very expensive in time and money and identification

of the strata may lead to classification of errors.

b) Disproportionate stratified random sampling: This method does not give

proportionate representation to strata. It necessarily involves giving over-

representation to some strata and under-representation to others. The

desirability of disproportionate sampling is usually determined by three factors,

viz, (a) the sizes of strata, (b) internal variances among strata, and (c) sampling

costs.

Suitability: This method is used when the population contains some small but important

subgroups, when certain groups are quite heterogeneous, while others are

homogeneous and when it is expected that there will be appreciable differences in the

response rates of the subgroups in the population.

Advantages: The advantages of this type is it is less time consuming and facilitates

giving appropriate weighing to particular groups which are small but more important.

Disadvantages: The disadvantage is that it does not give each stratum proportionate

representation, requires prior knowledge of composition of the population, is subject to

classification errors and its practical feasibility is doubtful.


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iii) Systematic Random Sampling: This method of sampling is an alternative to random

selection. It consists of taking kth item in the population after a random start with an

item form 1 to k. It is also known as fixed interval method. E.g., 1st, 11th, 21st

Strictly speaking, this method of sampling is not a probability sampling. It possesses

characteristics of randomness and some non-probability traits.

Suitability: Systematic selection can be applied to various populations such as students

in a class, houses in a street, telephone directory etc.

Advantages: The advantages are it is simpler than random sampling, easy to use, easy to

instruct, requires less time, its cheaper, easier to check, sample is spread evenly over

the population, and it is statistically more efficient.

Disadvantages: The disadvantages are it ignores all elements between two kth elements

selected, each element does not have equal chance of being selected, and this method

sometimes gives a biased sample.

Cluster Sampling It means random selection of sampling units consisting of population

elements. Each such sampling unit is a cluster of population elements. Then from each

selected sampling unit, a sample of population elements is drawn by either simple

random selection or stratified random selection. Where the element is not readily

available, the use of simple or stratified random sampling method would be too

expensive and time-consuming. In such cases cluster sampling is usually adopted. The

cluster sampling process involves: identify clusters, examine the nature of clusters, and

determine the number of stages.

Suitability: The application of cluster sampling is extensive in farm management

surveys, socio-economic surveys, rural credit surveys, demographic studies, ecological

studies, public opinion polls, and large scale surveys of political and social behavior,

attitude surveys and so on.

Advantages: The advantages of this method is it is easier and more convenient, cost of

this is much less, promotes the convenience of field work as it could be done in compact

places, it does not require more time, units of study can be readily substituted for other

units and it is more flexible.Disadvantages: The cluster sizes may vary and this variation could increase the bias of

the resulting sample. The sampling error in this method of sampling is greater and the

adjacent units of study tend to have more similar characteristics than do units distantly

apart.


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Area sampling

This is an important form of cluster sampling. In larger field surveys cluster consisting of

specific geographical areas like districts, talluks, villages or blocks in a city are randomly

drawn. As the geographical areas are selected as sampling units in such cases, their

sampling is called area sampling. It is not a separate method of sampling, but forms part

of cluster sampling.

Multi-stage and sub-sampling

In multi-stage sampling method, sampling is carried out in two or more stages. The

population is regarded as being composed of a number of second stage units and so

forth. That is, at each stage, a sampling unit is a cluster of the sampling units of the

subsequent stage. First, a sample of the first stage sampling units is drawn, then fromeach of the selected first stage sampling unit, a sample of the second stage sampling

units is drawn. The procedure continues down to the final sampling units or population

elements. Appropriate random sampling method is adopted at each stage. It is

appropriate where the population survey has to be made within a limited time and cost

budget. The major disadvantage is that the procedure of estimating sampling error and

cost advantage is complicated.

Sub-sampling is a part of multi-stage sampling process. In a multi-stage sampling, the

sampling in second and subsequent stage frames is called sub-sampling. Sub-sampling

balances the two conflicting effects of clustering i.e., cost and sampling errors.

Random Sampling with Probability Proportional to Size

The procedure of selecting clusters with probability Proportional to size (PPS) is widely

used. If one primary cluster has twice as large a population as another, it is give twice

the chance of being selected. If the same number of persons is then selected from each

of the selected clusters, the overall probability of any person will be the same. Thus PPS

is a better method for securing a representative sample of population elements in multi-

stage cluster sampling.

Advantages: The advantages are clusters of various sizes get proportionate

representation, PPS leads to greater precision than would a simple random sample ofclusters and a constant sampling fraction at the second stage, equal-sized samples from

each selected primary cluster are convenient for field work.

Disadvantages: PPS cannot be used if the sizes of the primary sampling clusters are not

known.


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Double Sampling and Multiphase Sampling

Double sampling refers to the subsection of the final sample form a pre-selected larger

sample that provided information for improving the final selection. When the procedure

is extended to more than two phases of selection, it is then, called multi-phase

sampling. This is also known as sequential sampling, as sub-sampling is done from a

main sample in phases. Double sampling or multiphase sampling is a compromise

solution for a dilemma posed by undesirable extremes. The statistics based on the

sample of n can be improved by using ancillary information from a wide base: but this

is too costly to obtain from the entire population of N elements. Instead, information is

obtained from a larger preliminary sample nL which includes the final sample.

Replicated or Interpenetrating SamplingIt involves selection of a certain number of sub-samples rather than one full sample

from a population. All the sub-samples should be drawn using the same sampling

technique and each is a self-contained and adequate sample of the population.

Replicated sampling can be used with any basic sampling technique: simple or stratified,

single or multi-stage or single or multiphase sampling. It provides a simple means of

calculating the sampling error. It is practical. The replicated samples can throw light on

variable non-sampling errors. But disadvantage is that it limits the amount of

stratification that can be employed.

Non-probability or Non Random Sampling

Non-probability sampling or non-random sampling is not based on the theory of

probability. This sampling does not provide a chance of selection to each population

element.

Advantages: The only merits of this type of sampling are simplicity, convenience and

low cost.

Disadvantages: The demerits are it does not ensure a selection chance to each

population unit. The selection probability sample may not be a representative one. The

selection probability is unknown. It suffers from sampling bias which will distort results.

The reasons for usage of this sampling are when there is no other feasible alternative

due to non-availability of a list of population, when the study does not aim at

generalizing the findings to the population, when the costs required for probability

sampling may be too large, when probability sampling required more time, but the time

constraints and the time limit for completing the study do not permit it. It may be


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classified into:

Convenience or Accidental Sampling

It means selecting sample units in a just hit and miss fashion E.g., interviewing people

whom we happen to meet. This sampling also means selecting whatever sampling units

are conveniently available, e.g., a teacher may select students in his class. This method

is also known as accidental sampling because the respondents whom the researcher

meets accidentally are included in the sample. Suitability: Though this type of sampling

has no status, it may be used for simple purposes such as testing ideas or gaining ideas

or rough impression about a subject of interest.

Advantage: It is the cheapest and simplest, it does not require a list of population and it

does not require any statistical expertise.

Disadvantage: The disadvantage is that it is highly biased because of researcherssubjectivity, it is the least reliable sampling method and the findings cannot be

generalized.

Purposive (or judgment) sampling

This method means deliberate selection of sample units that conform to some pre-

determined criteria. This is also known as judgment sampling. This involves selection of

cases which we judge as the most appropriate ones for the given study. It is based on

the judgement of the researcher or some expert. It does not aim at securing a cross

section of a population. The chance that a particular case be selected for the sample

depends on the subjective judgement of the researcher.

Suitability: This is used when what is important is the typicality and specific relevance of

the sampling units to the study and not their overall representativeness to the

population.

Advantage: It is less costly and more convenient and guarantees inclusion of relevant

elements in the sample.

Disadvantage: It is less efficient for generalizing, does not ensure the

representativeness, requires more prior extensive information and does not lend itself

for using inferential statistics.

Quota sampling

This is a form of convenient sampling involving selection of quota groups of accessible

sampling units by traits such as sex, age, social class, etc. it is a method of stratified

sampling in which the selection within strata is non-random. It is this Non-random

element that constitutes its greatest weakness.


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Suitability: It is used in studies like marketing surveys, opinion polls, and

readership surveys which do not aim at precision, but to get quickly some crude

results.

Advantage: It is less costly, takes less time, non need for a list of population, and

field work can easily be organized.

Disadvantage: It is impossible to estimate sampling error, strict control if field

work is difficult, and subject to a higher degree of classification.

Snow-ball sampling

This is the colourful name for a technique of Building up a list or a sample of a

special population by using an initial set of its members as informants. This

sampling technique may also be used in socio-metric studies.

Suitability: It is very useful in studying social groups, informal groups in a formalorganization, and diffusion of information among professional of various kinds.

Advantage: It is useful for smaller populations for which no frames are readily

available.

Disadvantage: The disadvantage is that it does not allow the use of probability

statistical methods. It is difficult to apply when the population is large. It does not

ensure the inclusion of all the elements in the list.

6. What is a Research Report? What are the contents of Research Report?

Research report is a means for communicating research experience to others. A

research report is a formal statement of the research process and it results. It narrates

the problem studied, methods used for studying it and the findings and conclusions of

the study. Research report is a method of businesses uses to identify patterns inconsumer buying and predicts future buying habits. It could potentially save a company

millions if they know whether consumers will be repulsed by, attracted to, or indifferent

to a product concept in development. These research reports can be developed in

several ways and for varying purposes.


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The first step in all research reports is to identify the purpose. All research reports are

designed to gather knowledge to make a more informed decision before investing

money into a concept, to determine the direction of a business venture or to decide

whether to eliminate a product or service. Identifying the purpose of the report helps to

direct the approach of the research-gathering efforts. The report may sell an idea or

change management's mind about an idea. Reports can also be used to identify and

rectify a problem within a company.

Contents of Research Report

I. Prefatory items Title Page

Declaration

Certificates

Preface/acknowledgements

Table of contents

List of tables

List of graphs/figures/charts

Abstract or synopsis

II. Body of the Report Introduction

Theoretical background of the topic

Statement of the problem

Review of the literature

The scope of the study

The objective of the study

Hypothesis to be tested

Definition of the concepts Models if any

Design of the study

Methodology

Method of data collection

Sources of data

Sampling plan


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Data collection instruments

Summary, conclusions and recommendations

III. Reference Material Bibliography

Appendix

Copies of data collection instruments

Technical details on sampling plan

Complex tables

Glossary of new terms used.


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ASSIGNMENT SET 2

1. Differentiate between nominal, ordinal, interval and ratio scales with an example of

each.

Nominal measurement - This level of measurement consists in assigning numerals or

symbols to different categories of a variable.

The example of male and female applicants to some planned activity is an example of

nominal measurement. The numerals or symbols are just labels and have no

quantitative value. The numbers of cases under each category are counted.

Nominal measurement is therefore the simplest level of measurement. It does not have

characteristics such as order, distance or arithmetic origin.

Ordinal measurement - In this level of measurement, persons or objects are assignednumerals which indicate ranks with respect to one or more properties, either in

ascending or descending order.

Example - Individuals may be ranked according to their socio-economic class, which is

measured by a combination of income, education, occupation and wealth.

The individual with the highest score might be assigned rank 1, the next highest rank 2,

and so on, or vice versa.

The numbers in this level of measurement indicate only rank order and not equal

distance or absolute quantities. This means that the distance between ranks 1 and 2 is

not necessarily equal to the distance between ranks 2 and 3.


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Ordinal scales may be constructed using rank order, rating and paired comparisons.

Variables that lend themselves to ordinal measurement include preferences, ratings of

organizations and economic status.

Statistical techniques that are commonly used to analyze ordinal scale data are the

median and rank order correlation coefficients.

Interval measurement - This level of measurement is more powerful than the nominal

and ordinal levels of measurement, since it has one additional characteristic equality

of distance. However, it does not have an origin or a true zero. This implies that it is not

possible to multiply or divide the numbers on an interval scale.

Example

The Centigrade or Fahrenheit temperature gauge is an example of the interval level of

measurement. A temperature of 50 degrees is exactly 10 degrees hotter than 40

degrees and 10 degrees cooler than 60 degrees.

Since interval scales are more powerful than nominal or ordinal scales, they also lend

themselves to more powerful statistical techniques, such as standard deviation, product

moment correlation and t tests and F tests of significance.

Ratio measurement -This is the highest level of measurement and is appropriate when

measuring characteristics which have an absolute zero point. This level of measurement

has all the three characteristics order, distance and origin.

Examples

Height, weight, distance and area. Since there is a natural zero, it is possible to

multiply and divide the numbers on a ratio scale. Apart from being able to use all the


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statistical techniques that are used with the nominal, ordinal and interval scales,

Techniques like the geometric mean and coefficient of variation may also be used.

The main limitation of ratio measurement is that it cannot be used for characteristics

such as leadership quality, happiness, satisfaction and other properties which do not

have natural zero points.

The different levels of measurement and their characteristics may be summed up.

In the table below

Levels of measurement CharacteristicsNominal No order, distance or origin

Ordinal Order, but no distance or origin

Interval Both order and distance, but no

origin

Ratio Order, distance and origin

2. What are the types of Hypothesis? Explain the procedure for testing Hypothesis.

A hypothesis is a tool of quantitative studies. It is a tentative and formal prediction

about the relationship between two or more variables in the population being studied,

and the hypothesis translates the research question into a prediction of expected

outcomes.

Concepts of Testing Hypotheses. Some basic concepts in the context of testing of

hypotheses are explained below -

1) Null Hypotheses and Alternative Hypotheses: In the context of statistical analysis, we


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often talk about null and alternative hypotheses. If we are to compare the superiority of

method A with that of method B and we proceed on the assumption that both 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 an alternative

hypothesis.

These are symbolically represented as:

Null hypothesis = H0 and Alternative hypothesis = Ha

Suppose we want to test the hypothesis that the population mean is equal to thehypothesized

mean ( H0) = 100. Then we would say that the null hypothesis is that the population

mean is equal to the hypothesized mean 100 and symbolically we can express it as: H0:

= H0=100

If our sample results do not support this null hypothesis, we should conclude that

something else is 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: = H0=100, we may consider three possible

alternative hypotheses as follows:

Alternative

Hypotheses

To be read as follows

Ha: H0 (The alternative hypothesis is that the population mean is not equal to 100

i.e., it may be more or less 100)

Ha: > H0 (The alternative hypothesis is that the population mean is greater than

100)


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3) Decision Rule or Test of Hypotheses: Given a hypothesis Ha and an alternative

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 items in it), against Ha, that the lot is not good (there

are many defective items in it), and 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 plan our 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 is known as a decision rule.

4) Type II Errors & I: 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 may accept

H0 when it is not true. The former is known as Type I and the latter is known 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 (alpha),

also called as level of significance of test; and Type II error is denoted by (beta).

Decision Accept H0 Reject H0 H0 (true) Correct decision Type I error ( error)

Ho (false) Type II error ( 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 5 chances in 100 that we will reject H0 when H0 is true. We can control

type I error just by fixing it at 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

committing type II error increases. Both types of errors cannot be reduced

simultaneously, since there is a trade-off in business situations. Decision makers decide

the appropriate level of type I error by examining the costs of penalties attached to both


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3. What are the advantages and disadvantages of Case Study Method? How is Case

Study method useful to Business Research?

CASE STUDY METHOD

The case study method is a very popular form of qualitative analysis and involves a

careful and complete observation of a social unit, be that unit a person, a family, an

institution, a cultural group or even the entire community.

Advantages

There are several advantages of the case study method that follow from the various

characteristics outlined above. Mention may be made here of the important

advantages.

(i) Being an exhaustive study of a social unit, the case study method enables

us to understand fully the behavior pattern of the concerned unit. In the

words of Charles Horton Cooley, case study deepens our perception and

gives us a clearer insight into life it gets at behavior directly and not by an

indirect and abstract approach.

(ii) Through case study a researcher can obtain a real and enlightened record

of personal experiences which would reveal mans inner strivings, tensions

and motivations that drive him to action along with the forces that direct him

to adopt ascertain pattern of behavior.


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(iii) This method enables the researcher to trace out the natural history of the

social unit and its relationship with the social factors and the forces involved

in its surrounding environment.

(iv) It helps in formulating relevant hypotheses along with the data which may

be helpful in testing them. Case studies, thus, enable the generalized

knowledge to get richer and richer.

(v) The method facilitates intensive study of social units which is generally not

possible if we use either the observation method or the method of collecting

information through schedules. This is the reason why case study method is

being frequently used, particularly in social researches.

(vi) Information collected under the case study method helps a lot to the

researcher in the task of constructing the appropriate questionnaire or

schedule for the said task requires thorough knowledge of the concerning

universe.

Disadvantages

(i) One of the main criticisms is that the data collected cannot necessarily be

generalized to the wider population. This leads to data being collected over

longitudinal case studies not always being relevant or particularly useful.

(ii) Some case studies are not scientific. Freud used case studies for many of

his theories or studies. Such examples are that of Anna O and Little Hans.

Both of these are not scientific nor are they able to be generalized. This can

be attributed to them being case studies, but also Freudian theory in general.


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(iii) Case studies are generally on one person, but there also tends to only be

one experimenter collecting the data. This can lead to bias in data collection,

which can influence results more than in different designs.

(iv) It is also very difficult to draw a definite cause/effect from case studies.

Case study method is useful to businesses which are mentioned above in the

advantages of case study method overall, case studies are an important and useful

method of data collection, especially in cases of rare phenomena. It would be extremely

unethical to go taking parts of peoples brains out just to make a larger sample size to

use a different experimental design method. However, as data is collected on new cases

I think it is important to always refer back to previous data in order to build on existing

knowledge and ensure findings are as applicable to real life as possible.

4. What are the Primary and Secondary sources of Data?

Primary sources - A primary source is an original object or document -- the raw material

or first-hand information. Primary sources include historical and legal documents,

eyewitness accounts, results of experiments, statistical data, pieces of creative writing,

and art objects. In the natural and social sciences, primary sources are often empirical

studies -- research where an experiment was done or a direct observation was made.

The results of empirical studies are typically found in scholarly articles or papers

delivered at conferences, so those articles and papers that present the original results

are considered primary sources.


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Primary sources can include

Interviews, diaries, letters, journals, speeches, autobiographies, and witness

statements

Articles containing original research, data, or findings never before shared

Original hand-written manuscripts

Government documents and public records

Art, photographs, films, maps, fiction, and music

Newspaper and magazine clippings

Artifacts, buildings, furniture, and clothing

Secondary sources - A secondary source is something written about a primary source.

Secondary sources include comments on, interpretations of, or discussions about the

original material. You can think of secondary sources as second-hand information. If I

tell you something, I am the primary source. If you tell someone else what I told you,

you are the secondary source. Secondary source materials can be articles in newspapers

or popular magazines, book or movie reviews, or articles found in scholarly journals that

discuss or evaluate someone else's original research.Secondary sources can include

Textbooks

Review articles and critical analysis essays

Biographies

Historical films, music, and art Articles about people and events from the past


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5. Differentiate between Schedules and Questionnaire. What are the alternativemodes of sending Questionnaires?

Difference between questionnaires and schedules

Both questionnaire and schedule are popularly used methods of collecting data in

research surveys. There is much resemblance in the nature of these two methods and

this fact has made many people to remark that from a practical point of view

A questionnaire will feature a series of queries which must be answered by a person,

whereas a schedule is a listing of events and meetings over a defined period.

A questionnaire may also be called a survey, and it is used to collect information about

specific subjects. Often, questionnaire may be used for the following purposes:

Reasons to Use a Questionnaire

Marketing Campaigns - Commonly, marketing executives will use questionnaires to get

valuable feedback from customers or potential clients. By getting answers to

questions that pertain to a business concern or market sub-segment, marketing

executives can prepare timely and relevant ad campaigns that meet the needs of theirtarget demographic. Sometimes, marketing executives will pay people to fill out

questionnaires. At other times, these will be filled out voluntarily, for no compensation.

Healthcare - In clinics or hospitals, patients seeking healthcare are often asked to fill

out questionnaires that outline their medical histories, habits, and needs. These sorts


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of questionnaires allow medical professionals to achieve accurate diagnoses, and to

design courses of treatment that are safe and effective.

Reasons for Using Schedules

Organization - A schedule can be an essential component of time management; for

example, knowing what is happening during a weekly, bi-weekly, or monthly period will

allow a person to plan ahead and be prepared for every circumstance. Without a

schedule, appointments may be forgotten, or important events may be missed.

Goal Setting - By analyzing a schedule, a person can determine whether or not they are

moving closer to his or her goals. For example, if a person wants to get fitter, he or she

can track their workouts via a schedule, and record results based on the success of their

regimen over time.

Both questionnaire and schedule are popularly used methods of collecting data in

research surveys. There is much resemblance in the nature of these two methods and

this fact has made many people to remark that from a practical point of view, the two

methods can be taken to be the same. But from the technical point of view there is

difference between the two.


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1.Questionnaire is generally sent through mail to

informants to be answered

1. Schedules is generally filled by the research

worker or enumerator, who can interpret the

questions when necessary

2. Data collection is cheap 2. Data collection is more expensive as money is

spent on enumerators

3. Non response is usually high as many people

do not respond

3. Non response is very low because this is filled by

enumerators

4. It is not clear that who replies 4. Identity of respondent is known

5. The questionnaire method is likely to be very

slow since many respondents do not return the

questionnaire

5. Information is collected well in time

6. No personal contact is possible in case of

questionnaire

6. Direct personal contact is established

6. Explain the various steps in processing of Data.

Data is an integral part of all business processes. It is the invisible backbone that

supports all the operations and activities within a business. Without access to relevant

data, businesses would get completely paralyzed. This is because quality data helps

formulate effective business strategies and fruitful business decisions.

Therefore, the quality of data should be maintained in good condition in order to

facilitate smooth business proceedings. In order to enhance business proceedings, data


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should be made available in all possible forms in order to increase the accessibility of

the same.

Data processing refers to the process of converting data from one format to another. It

transforms plain data into valuable information and information into data. Clients can

supply data in a variety of forms, be it excels sheets, audio devices, or plain printed

material. Data processing services take the raw data and process it accordingly to

produce sensible information. The various applications of data processing can convert

raw data into useful information that can be used further for business processes.

Companies and organizations across the world make use of data processing services in

order to facilitate their market research interests. Data consists of facts and figures,

based on which important conclusions can be drawn. When companies and

organizations have access to useful information, they can utilize it for strategizing

powerful business moves that would eventually increase the company revenue and

decrease the costs, thus expanding the profit margins. Data processing ensures that the

data is presented in a clean and systematic manner and is easy to understand and be

used for further purposes.

Here are the 5 steps that are included in data processing:

Editing - There is a big difference between data and useful data. While there are huge

volumes of data available on the internet, useful data has to be extracted from the huge

volumes of the same. Extracting relevant data is one of the core procedures of data

processing. When data has been accumulated from various sources, it is edited in order

to discard the inappropriate data and retain relevant data.


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Coding - Even after the editing process, the available data is not in any specific order. To

make it more sensible and usable for further use, it needs to be aligned into a particular

system. The method of coding ensures just that and arranges data in a comprehendible

format. The process is also known as netting or bucketing.

Data Entry- After the data has been properly arranged and coded, it is entered into the

software that performs the eventual cross tabulation. Data entry professionals do the

task efficiently.

Validation - After the cleansing phase, comes the validation process. Data validation

refers to the process of thoroughly checking the collected data to ensure optimal quality

levels. All the accumulated data is double checked in order to ensure that it contains no

inconsistencies and is utterly relevant.

Tabulation - This is the final step in data processing. The final product i.e. the data is

tabulated and arranged in a systematic format so that it can be further analyzed.

All these processes make up the complete data processing activity which ensures the

said data is available for access.

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