Research Process SPC

8/2/2019 Research Process SPC

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Dr.R.VASANTHAGOPALAssociate Professor

P.G &Research Dept. of Commerce

The Cochin College Kochi-682 002

[email protected]

Research Process in

Social Science


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Research Vs Research Methodology

17/12/2010Dr.R.Vasanthagopal,The Cochin College, Kochi-22

A search for facts- answer to questions andsolutions to problems

Organized enquiry- explanation to unexplainedphenomenon through scientific rather than

arbitrary(unscientific) methodThus, research is an organised set of activities to

find practical solution for a realistic problemsupported by data.

Research methodology is a system of models,procedures and techniques used to find the resultsof a research problem.


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Social Science Research


Sciences are-Natural (Physical) sciences andSocial sciences.

Social sciences deal with human life, humanbehaviour, social groups and social institutions.

As it deals human nature and mans environmentit is more difficult to comprehend than the physicalphenomena.

It seeks to find solution to unsolved social

phenomena to clarify the doubtful, and correct themisconceived facts of social life(Pauline V Young).


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Requisites for Social Science Research


Existence of a realistic problem Systematic analysis of the problem with dataDefine terms, concepts, statistical tools unequivocallyCollection of data relevant to the problem under studyClassification of data Identify and state variablesUse appropriate statistical procedure in summarizing the

data Set hypothesis for the population and also test the

hypothesis using appropriate tool

Conclusion and generalization based on findingsComplete elimination of personal equationComplete and careful reporting of the research process


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Process in Social Science Research


Problem definition

Objectives of research

Research design

Data collectionData analysis and interpretation


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Problem Definition


Selection of a problem is the first step in research

Problemmeans a question/issue to be examined

The problem must be identified and defined

without ambiguity.One with a critical, curious and imaginative mind

and is sensitive to practical problems could easily

identify problems

Ill-defined problems may end up with misleadingconclusions


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Objectives of Research


Objectives set should be able to give solution to theresearch problem

Objectives may be-Quantitative and QualitativeQuantitative objective aims to maximize the

performance of the aspect under study.

Qualitative objective aims to test the significance ofhypotheses.

set objectives based on:Research questions- are the problems which are not resolved

till data

Hypothesis- assumption about a population of the studyBoundary of the study- define the boundary clearly. Size,

complexities and constraints are the important considerations.


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Research Design


A logical plan prepared for directing a research study.It provides a complete guidelines for data collection.Essence of a design

Selection of a research approach- Based on therequirements decide the type of study

Design of sampling plan- may be probability and non-probability sampling

Design of experiment- Identify variables and assess theirimpact

Design of questionnaire- It is necessary in case of empirical

studiesThe success of a survey based research depends onthe strength of the questionnaire.


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Data Collection


Social scientists make use of both primary andsecondary data

Without data no specific inferences can be drawnon the problem under study.

The relevance, adequacy and reliability of datadetermine the quality of the findings of a study

The researcher should evaluate thequality(reliability, accuracy and completeness) of

secondary data before its use.The methods of collecting primary data depend on

population, time, cost, precision required, etc.


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Data Analysis

The process of evaluating data using analyticaland logical reasoning to examine each componentof the data provided to form some sort offinding orconclusion.

Data analysis is just one of the many steps thatmust be completed when conducting a researchstudy.

The computer will assist in the summarization of

data, but statistical data analysis focuses on theinterpretation of the output to make inferences andpredictions.

17/12/201010 Dr.R.Vasanthagopal,The Cochin College, Kochi-2


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Why Data Analysis?

Data (crude information)-Information-Facts (arewhat the data reveals)-Knowledge

Decisions under uncertainty

Increase the level of improvements in decision-

making

Place knowledge on a systematic evidence base

Forecast and predict future aspects of a business

operation



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Types of Data Analysis-1


Secondary Data AnalysisPrimary (Survey) Data Analysis

Data source for a research study may be of two-

Secondary and Primary

Using secondary data in a research study enablesto give a strong theoretical base for the problemunder study. Descriptive statistics viz. averages,percentages, measures of dispersion are largely

used for analysing the secondary datacont


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Analyzing survey results require strict attention todetail and, in some cases, knowledge of statistics andcomputer software packages. How you conduct thesesteps will depend on the scope of your study, your owncapabilities, and the audience to whom you wish to

direct the work.Before actually beginning the survey the researcher

should know how they want to analyze the data. Besure to pick your program before you design your

survey. some programs require the data to be laid outin different ways.

Conti..


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After the survey is conducted and the datacollected, the results must be assembled in some

useable format that allows comparison within the

survey group, between groups, or both.

The results could be analyzed in a number of

ways. It all dependence on the nature of the data,

size of the sample, scale, amount of precision

required etc.


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Concepts in Data Analysis


PopulationAll Units/objects/individuals understudy(Denoted by N)Sample

A Part of a population (Denoted by n)

VariableCharacteristics of an individual or object Dependent,

independent and extraneousParameter

Characteristics of the populationStatistic

Characteristic of the sample


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Data Analysis-Process-1(In Empirical Research)

Defining the problem- It is extremely difficult to gatherdata without a clear definition of the problem

PopulationSample

Collection of data- Designing ways to collect data is animportant job in statistical data analysis

Data Entry (Either in SPSS/STATA/EXEL)

Data Analysis(Either in SPSS or STATA-Statistical

software packages)

cont



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There are two methods for analyzing data-1.Exploratory methods and 2.Confirmatory

methods

Exploratory methods use simple arithmetic and

easy-to-draw pictures to summarize data.

Confirmatory methods use ideas from probability

theory in to answer specific questions. It provides

a mechanism for measuring, expressing, and

analyzing the uncertainties associated with futureevents. The majority of the topics of research fall

under this method. Cont

17 Dr.R.Vasanthagopal,The Cochin College, Kochi-2 17/12/2010


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Exploratory and Confirmatory methods include:1.Descriptive analysis 2.Univeriate analysis 3.Bi-

variate analysis 4.Multivariate analysis

Interpretation

Reporting the results- The results may be reported

in the form of a table, a graph or a set of

percentages.


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Qualitative Vs Quantitative Data

Qualitative(Categorical)Data

QuantitativeData


Make a frequency

table

Bar diagram/Pie

diagram(for graphical

representation)

Obtain the modified

range item divide in to

several classMake a frequency

table

Histogram/pie diagram


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Statistical Scales


Social science research deal with varioussocial/psychological variables

Their measurement is one of the vital stages

in the research processNominal

Ordinal

Interval

Ratio


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Nominal Scale(Lowest level of measurement)


CharacteristicsNo order, distance or arithmetic origin(uniqueorigin indicated by zero)Measurement Principle

People/objects with the same scale valueEg.sex,religion.caste,etc (Assign numerals sayI,2,3..These are just labels and have no quantitative value)

Permissible Arithmetic operations

CountingAppropriate statisticsMode, Chi square


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Ordinal Scale


CharacteristicsOrder, but no distance or arithmetic origin

Measurement Principle

People/objects are ordered by rank from least to most

on a continuum (either in ascending/descending orders)


Greater than/less than operations

Appropriate statisticsMedian, Inter Quartile range, Weighted mean, Rank

correlation


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Interval scale


CharacteristicsBoth order and distance, but no arithmetic origin


Objects with Intervals value

Eg.Temparature,Time


Addition/substraction of scale valuesAppropriate statistics

Mean, SD, t-test, f-test, ANOVA,MANOVA, FactorAnalysis, Regression ,Multiple Correlation


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Ratio Scale(Highest level of measurement)


CharacteristicsOrder, distance and arithmetic origin


There is a rationale(natural)zero point for the scale

Eg.weight,height,distance,money value,rate of returnPermissible Arithmetic operations

Addition,substraction,multiplication and division ofscale values

Appropriate statistics

All techniques usable at nominal, ordinal and intervallevel, GM,HM,Co-efficient of variation.

(CV=SD/Mean)


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Types Statistical Analysis


Descriptive AnalysisDescribes the nature of an object/phenomenonunder study viz. profile of the sampleindividual/organisation,workgroups etc.

This analysis may describe data on one variable,two variables and more than twovariables(Accordingly called univariate, bivariateand multivariate analysis)

Inferential AnalysisDrawing inferences and conclusions from the findingsof a research study.


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Hypothesis Testing-1


Hypothesis is an assumption about a population.There are two types of hypothesis-Null

hypothesis(Ho) and Alternate hypothesis(H1).Null hypothesis is a statement of no change or no

difference or no relationship. It is a preferredassumption. The hypothesis representing theopposite of the null hypothesis is alternatehypothesis.

Both the null and alternate(research) hypothesesare expressed in terms of the populationparameters, not in terms of the sample statistics.


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Hypothesis Testing-2


It is the null hypothesis that is tested directly; theresearch hypothesis is supported when the null

hypothesis is rejected.

Hypothesis testing means subjecting a hypothesis

to an appropriate empirical scrutiny and statisticaltest to determine its validity.

The hypothesis formulated should be testable i.e.

amenable for empirical investigation.


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Hypothesis Testing-Steps


Identify Ho and H1Select the test statistic and determine its

value(observed value) from the sample dataCompare the observed value and the critical

value(table value)Make a decisionIf the observed value> the critical value=Significant

(Reject Ho)

If the observed value< the critical value=Notsignificant

(Accept the Ho)


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Significance Level and Sampling Error


Significance level is the probability with which theHo is rejected due to sampling error, though Ho is

true.

Sampling error may be of two-Type-1 error(Alpha)=Probability of rejecting Ho when it is true

Type-2 error(Beta)=Probability of accepting Ho when it is false

Decision Ho True Ho False

Reject Ho Type I error No error

Accept Ho No error Type II error


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Statistical Tests and Applications

17/12/2010

Dr.R.Vasanthagopal,The Cochin College, Kochi-231

No.of sample Scale t-test F test Chi square ANOVA

Hypothesis about frequencydistribution

Hypothesis about mean

1,2 or more

One large

sample(n>30;n is knownOne sample(smallsample)

Two(large sample)

Two(smallsample)

Three or more

Nominal

Interval/Ratio

Interval/Ratio

Interval/Ratio

Interval/Ratio

Interval/Ratio

Hypothesis about proportionOne sample(large)

One sample(small)

Two sample(large)

Two sample(small)

Interval/Ratio

Interval/Ratio

Interval/Ratio

Interval/Ratio

Hypothesis about variation Two or more sample Interval/Ratio


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Tests of Significance-1


Parametric and non-parametricParametric tests More power full but depend on the parameters/characteristics of

the population

Values must be independent(selection one item must notdepend upon other item)

Distribution must be normal

The population should have equal variances

Scale: Interval

Important Tests: t-test, z-test(testing the mean, median, mode,

correlation etc.) and F-test


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Tests of Significance-2


Non-parametric testsAre population free tests as they are not based on

parameters/characteristics of the population

Values must be dependent(selection one item must depend

upon other item)

Distribution may not be normal

The population should not have equal variances

Scale: Ordinal/nominal

Important Tests: chi-square test, median test, sign test,

KS(Kolmogorow Smirnov) test.


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Chi-square Test-Illustration


Income Education

Low High Total

Low 30 12 42

High

Total

10

40

28

40

38

80

Income Education

Low High Total

Low 30(21)* 12(21) 42

High

Total

10(19)

40

28(19)

40

38

80


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Meaning and Interpretation of p-value


A p-value is a measure of how much evidence youhave against the null hypothesis. The smaller thep-value, the more evidence you have.

If the p-value is less than some threshold (usually .

05) then reject the null hypothesis.P-value Interpretation Sig/Not sig. Decision

p


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Reference


1. Alan Agresti and Barbara Finley(1997), StatisticalMethods for the SocialSciences ,Prentice-Hall, New

Delhi.

2. Krishnaswami,O.RandM.Ranganathan(2009),Methodology of Research in social Sciences, Himalaya

Publishing House, New Delhi.

3. Paneerselvam,R(2005),ResearchMethodology,Prenti

ce-Hall of India, New Delhi.


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Thank

you

17/12/2010Dr R Vasanthagopal The Cochin College Kochi 237

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Research Process SPC