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Research Design
Once the research problem is identified, clearlystated, theoretical framework built and thehypothesis explicated, the variables defined, thereis a need to construct a proper research design.
These are the basic requirements which theresearcher must have in hand before planning anyresearch activity.
Research design is a plan of action; a conceptualstructure within which a research is conducted.
Definition: a research design is the arrangementsof conditions for collection and analysis of data in amanner that it aims to combine relevance to theresearch purpose with economy.
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Research Design
Need for research design: When we are constructing a house, we need a
blue print (map) of the house so that the houseis constructed with attractive look, and with
proper expenditure of the money.
The same is the case with a research design. Itis a blue-print, which facilitates the variousoperations of research in an efficient andeconomic way.
Research design stands for advanced planningof the methods to be adopted for conductingresearch keeping in view the objectives of theresearch & available time & resources.
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Research Design
Research Design is a plan, structure,and strategy of investigation soconceived as to obtain answers to RQs
or Hypothesis. It is a complete scheme of the research
It includes an outline of what theinvestigator will do from writing the
hypothesis and their operationalimplications to the final analysis ofdata.
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Research Design
Components of a research design
A research design mainly has the following
components:
A clear statement of the research problem(Observational design)
The population to be studied (sampling design)
Procedures and techniques to be used for datacollection (operational design)
Methods to be used for data processing andanalysis (statistical design)
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Research Design
Observational: it relates the conditionsunder which observations are made i.e.a clear statement of the research
problem Sampling: Universe, sampling unit,
sample size
Operational: data sources, tools, time,
budget (cost consideration)
Statistical: Analytical techniques
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Research Design
The following steps in the design must rigidly befollowed:
Objectives of the study
Data collection methods Selection of sample Data collection (from where and time period) Data analysis Reporting the findings
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Research Design
Hypothesis testing studies: also knownas experimental studies;
Are those in which the researcher tests
the hypotheses for casual relationshipsbetween the variables.
Causal study: where the researcher isinterested to find the cause/effects ofone or more problems
Correlational study: where theresearcher is interested to delineate therelationships of two or more variables.
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Research Design
Components of a research design Methodology and Research design:
Methodology means the procedure used forresearch. It may include all steps from selection
of the problem to interpretation of the findingsDesign:
Universe of the study: where to conduct Sample selection: who will be the respondents Research Method: which method
Data sources Tools for data collection Analytical techniques
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Sampling Design
Data refers to a collection of organizedinformation, usually the results ofexperience, observation or experiment or
a set of premises.
This may consist of numbers, words, orimages, particularly as measurements or
observations of a set of variables.
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Sampling Design
Sources of Data:
Two main sources:
Primary and Secondary: Primary data:
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Sampling Design
Primary Data sources
The data that can be freshly
obtained from the respondentsduring the actual field work orthrough observation
Secondary data sources:
The data which is gathered fromthe sources already existing.
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Sampling Design
Sources of primary data
Four sources;
Individuals, groups,
Panels and
unobtrusive sources.
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Sampling Design
Individuals:
Primary data from individuals can be collected inthe form of interviews, through questionnaires orthrough observation.
Focus groups: a specific group of people whoare experts on the topic on which informationare sought is called focus group. A groupnormally has one moderator and informationfrom the group is collected through discussions
on a particular topic. Focus groups are relatively inexpensive and
provide data in short time.
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Sampling Design
Panels are also group of specific people. Thedifference between group and panel is that thepanel meets more than once and information isrecorded from them. Panel studies are
conducted in case when the effects of certaininterventions or changes are to be studied overa period of time.
Static and dynamic panels:
Static: same members serve on panel over long
period of time Dynamic: panel members change from time to
time as various phases of study are in progress.
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Sampling Design
Unobtrusive sources:
Source which does not involve people.
For example: the personal records of
employees of a company
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Sampling Design
Secondary Source: The data which the researcher does not
collect newly but take it from some oneother than him is called secondary data.
Sources of secondary data: books,journals, government publications, database, census data, statistical companiesetc.
Advantages: saving cost and time Disadvantage: obsolete, not exactlyaccording to the needs
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Sampling Design
Types of surveys (studies): two types From the research universe, a pre-determined
population is selected, from which informationand data is to be collected.
If we take the whole population for datacollection, is called census inquiry.
However, if the population is large, then we takesome portion (respondents, elements, items) ofthe whole population which is called sample.
The process is called sampling technique andthe survey is called sampling survey.
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Sampling Design
Sample design:
A sample design is a definite plan ofobtaining a sample from a given
population. Sample design may lay downthe number of items to be included in thesample i.e. the size of the sample.
Sample design is determined before thedata is collected.
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Sampling Design
Steps in sample design: Type of universe: the first step in developing a
sample design is to clearly define the set ofobjects to be studied; called universe of study.
Universe can be finite and infinite. For example;the employees in an organization; whereasinfinite as coca cola drinkers in a region.
Sample selection (sampling unit): beforeselecting the sample size, a sample unit has to
be defined. It could be a geographical unit suchas a city, district; or a construction unit such asa household; or a social unit such as a family orschool; or an individual.
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Sampling Design Sampling frame / population frame: also called as
source list: u have universe, sample unit; u needthe list of names of all items in the universe. Fromthat list u have to draw your sample. If the sourcelist is not available, the researcher has to make it.
Sample size: it refers to the number of items to be
studied from the universe. The sample size shouldneither be too large; nor be too small. It should beoptimum. Optimum sample size is that which fulfilsthe requirements of the efficiency,representativeness, reliability and flexibility.
Parameters of interest: Specific parameters of
interest must be considered before determiningsample design. For example certain characteristicsof population which are of your interest.
Budgetary constraints: Cost consideration hasimportant impact upon decision relating to samplesection.
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Sampling Design
Types of sample design:Two main types of sample design:
Non-probability sampling:
In non-probability sampling procedure,the researcher purposively choose theparticular units of the universe forconstituting the sample on the basis thatthe small mass that they select of a
huge one will be typical orrepresentative of the whole. In this type of sampling, the items are
selected deliberately by the researcher
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Sampling Design
Types of non-probability sample design:
Convenience sampling: Convenience sampling refers tothe collection of information from members of thepopulation who are easily available to the researcher.
Purposive sampling: In this type of sampling, instead oftaking respondents easily available, the researcher takessome specific types of people as sample. Purposivesampling may be:
Judgement sampling: in this sampling, a specific groupwho is considered to be in best position to provide somespecific information.
Quota sampling: in quota sampling a predeterminedproportion of the people are sampled from differentgroups.
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Sampling Design
Probability sampling:
Under this sampling design; every itemof the population has equal chance of
inclusion in the sample. Also called asrandom sampling or chance sampling.
The results obtained through probabilitysampling are considered as more reliable
than the non-probability samplingbecause the element of bias is lessincluded.
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Sampling Design
Types of probability sampling:
Simple random sampling or unrestrictedsampling:
Every element of the population has a knownand equal chance of being selected. Also knownas unrestricted probability sampling.
Advantages: Has least bias and offers mostgeneralizability.
Disadvantages: difficult, lengthy and expensive
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Sampling Design
Complex random sampling or restricted sampling:
Other than simple random sampling, complex randomsampling design is also used. Also called restrictedprobability design or mixed sampling design.
Types of complex random sampling design: Systematic sampling: In some cases, sampling is done in a way that every ith
element in the population is included in the sample. Thisis called systematic sampling. The element ofrandomization is introduced by picking up the unit formwhich to start randomly.
Systematic sampling is done when list of population isavailable and is of considerable length.
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Sampling Design
Stratified random sampling: If the population from which the sample has to be drawn
does not constitute a homogeneous group, stratifiedsampling technique is used in order to obtainrepresentative sample.
Under stratified sampling, population is divided intoseveral subgroups called strata. Items from eachstratum are selected to constitute sampling.
For example; if a researcher is interested to study thebehaviour of employees in an organization; includesemployees from all categories; management, lowermanagement, clerical staff, etc.
proportionate stratified sampling: disproportionate stratified sampling
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Sampling Design
Cluster sampling:If the group or population is large andthere exists heterogeneity among the members within eachgroup, then we divide the population into sub-groups calledclusters. The sampling from clusters is called clustersampling.
However, this sampling technique is not very common inorganizational research.
Area sampling: If the clusters happen to be a geographicunit; the sampling design is called area sampling design.
Multistage sampling: if sampling is once done, information
is gathered and further detailed information is requiredfrom the sub sample of the same sample; the sampling iscalled multi-stage sampling.
Could be double stage sampling or three-stage samplingdesign.
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Sampling Design
Sources of Data: Normally, there are three methods of
data collection: 1. To observe the behaviour of persons,
groups or organizations and theiroutcome
2. To ask questions from theindividuals.. Field work primarydata (through communication)
3. To utilize the existing record or dataalready generated for other purposes..Library research..secondary data
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Sampling Design
Data collection methods:
There are different ways used for data collection. Thechoice of data collection method depends on theavailable resources, the degree of accuracy required,
the expertise of the researcher, the time span of thestudy, other costs and resources associated with datagathering.
Data is mainly collected through the followingmethods:
Interview method Questionnaire method Observations
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Sampling Design
Observation:
The habit, practice or faculty of seeingand noting; the act of noting andrecognizing the phenomena as theyoccur in nature.
The method of collecting informationby seeing and noting.
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Sampling Design
Types of observational research:
Participant observation: if the researcherbecomes a part of the working team
Non-participant observation: theresearcher observes the individuals inthe work place without becoming a partof the organizational system.
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Sampling Design
Structured observational studies: if the observer has a predetermined set of
categories to be observed; the study is calledstructured observational study.
Unstructured observational study:
if the researcher has no specific ideas of theparticular aspects that need focus; theresearcher records everything he notices.Such study is called unstructuredobservational study.
Such studies are normally done if qualitativeresearch is aimed.
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Sampling Design
Uncontrolled observation:
if the observation takes place in the naturalsetting; may be termed as uncontrolled
observation.
controlled observation
But if the observations take place according topre-arranged plans, involving experimentalprocedure, the observation is called controlledobservation.
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Sampling Design
Interview methods:
In this method, information is collected from therespondents through interviewing him/her. Interview couldbe:
Unstructured interviews: in this type of interviews, theinterviewer does not have a planned set of questions to beasked from the respondents. Unstructured interviews arecarried out when some preliminary information gathering isdesired. In such interviews normally broad open endedquestions are asked. The type and nature of questionsasked may vary from individual to individual, dependingupon their job position (level) and type of job he is doing.
For example: what is your opinion about.. When a number of unstructured interviews are conducted,
the researcher gets a fair idea of what variables areimportant for the in-depth consideration.
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Sampling Design
Structured interviews:
Structured interviews are conducted when it isknown that what specific information is needed.The interviewer has a list of pre-determined
questions to be asked from the respondents.The focus is on the factors that were surfacedduring the unstructured interviews. The samequestions are asked form other people as well.
After conducting sufficient number of structuredinterviews, the information obtained aretabulated and data is analysed
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Sampling Design
Forms of interviews
Face to face interviews;
Telephonic interviews;
Computer assisted interviews;
And interviews through electronicmedia;
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Sampling Design
Most of the unstructured interviews areconducted face to face.
Structured interviews could either be
face to face or through other mediumssuch as telephone. Telephonic interviewsare best suited if the number ofrespondents is small but distant or if the
number of respondents is large andwidely scattered or if the duration of theinterview is too short.
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Sampling Design
Face to face interview:
Advantages: as direct, so theresearcher can clarify doubts ofthe respondents, can rephrasethe question and can note thenon-verbal cues that therespondents produces.
Dis-advantage: more expensiveand timely
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Sampling Design
telephonic interview:
Advantages: different people can
be interviewed in short time, lesscostly
Dis-advantage: if the intervieweefeel dis-comfort, will terminatethe call
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Sampling Design
2. Questionnaires:
Questionnaire is a pre formulatedwritten set of questions to which
respondents record their answers.Questionnaire is an effective datacollection mechanism if the researcherknows exactly what is required and howto measure the variables of interest.
Personally administered: Mail questionnaires:
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Sampling Design
Getting data ready for analysis: After collection, the data has to be analysed in
accordance with the outline laid down for the purposeat the time of developing the research plan. Butbefore analysis, the data needs to be processed andmade reading for analysis. Data processing implies
editing, coding, classification and tabulation of datacollected.
Data analysis refers to the computation of certainmeasures along with searching for patterns ofrelationship that exists among data groups.
In analysis, the relationship or differences supportingor conflicting with original or new hypothesis shouldbe subjected to statistical tests of significance todetermine with what validity the data can be said toindicate any conclusion.
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Sampling Design
Processing Operations: Processing of data (also called as data
testament) includes the following steps: Data sifting: which includes: Editing: when the data is collected, it is
called raw data. It is necessary toexamine the data so that to detect andcorrect errors and omissions which mayoccur during hurry in field. This is calleddata editing.
Editing is done to ensure that the dataare accurate, consistent, uniformlyentered, and as completed as possible.
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Sampling Design
Coding: after editing, the data is being coded.
Coding can be defined as the process of classifyingresponses into meaningful categories.
Example: education:
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Sampling Design
Classification: also called categorization: to getmeaningful relationship, a large volume of the rawdata is to be classified into different broadcategories. Classification is the system of
arranging data in groups or identifiable classes onthe basis of common characteristics.
For example: male and female; skilled andunskilled
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Sampling Design
Tabulation
After data treatment, the data is shifted fromquestionnaires to the data sheets. This caneither be done manually or in computers. This is
called data entry or data tabulation.
analysis: After data entry; the data is analysed.
Mostly we see either causal relations or inter-relations. In causal relations, we see that how
one variable affects the other. This is donethrough regression analysis.
If we have to see the inter-relation of twovariables and their effects; correlation analysisis done.