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Research Methodology
Rajbir Singh, Ph.D.
Professor of Psychology
Maharshi Dayanand University,
Rohtak
 Functions of Research
Description
Explanation
Prediction
Control
 Type of Research
Context
Discovery V/s Justification
Pure v/s Applied
Research : A Process
 In sciences we conduct research in order to
determine the acceptability of
hypotheses derived from theories.
Having selected a certain hypothesis which
seems important in a certain theory, we
collect empirical data which should yield
direct information on the acceptability of
that hypothesis. Our decision about the
meaning of the data may lead us to retain,
revise, or reject the hypothesis and
even the theory which was its source.
The Methodology cycle
Theory
Hypothesis
Data
Analysis
Exhibit: Research as a process (Bidirectional)
Sources of Data
 Primary-When a researcher himself/herself
observes the phenomenon and records with
the help of tools or otherwise under natural
or controlled conditions.
 Secondary – Collecting from primary
sources, e.g. census reports , remote
sensing , cumulative records etc.
Frequently Asked Questions in Research
1. When analysis?
When having data/information and to draw inference
2. What type of data?
Qualitative/Quantitative?
3. If qualitative what type?
Narratives -Verbal
Product- Non-Verbal
Performance
4. If quantitative what is the Level of
measurement ?
Nominal, Ordinal, Interval and Ratio Scale
5. What Kind of Sample?
Large/Small:n1, ....N=30,----N
6. How the sample has been drawn?
Probability
Non-probability
7. Estimation of population parameters? µ, σ
8. Verification of hypothesis, if any ?
9. Correlational/ Experimental ?
10. Parametric/Nonparametric ?
11. Univariate/bivariate/multivariate ?
Analysis of Data
A. Descriptive Presentation
n=1,
Xs-listing, ordering, bunching, categorization
Mean, Median, Percentile, Quartile etc.
Mode: Uni/bimodal/Multimodal
Distribution- frequencies, class intervals
SD, Range,SEM
Graphic presentation- Bar diagrams, pie-charts etc.
Histogram/polygon
Data transformation- monotonic , uni-directional,calculative
distress:
√X, 1/ X,, log transformation, Arcsine transformation,
X+…, X-… etc.
 Normalization e.g. T-scaling (M=50,SD=10)
B. Pre-Verification Test
 Test of deviation from normality-Skewness
and Kurtosis
 Test of homogeneity- Bartlett's test, Cochran's
test
 Test of homosedacity –
Range restriction-Comparing distribution
 Data scanning for assumptions-
 Linearity , Independence , Sphericity , Additivity etc.
C. Verification of Hypothesis/ Goodness of fit
 Statistical test yields a value that has associated
probability alpha, the level of significance ( the p
of making type I error, i.e.; rejecting null
hypothesis when it is true). Beta, the p of type
II error, accepting null hypothesis when it is in
fact false. Alpha is inversely related to beta, so
to reduce these errors, we must increase N.
 Sample mean and SD should be equal to
population parameters. Are they or are not?
Sampling distribution of various statistic has p of
mean and SD to approximate of µ and σ. It is
the process of estimation.
Some common Tests for verification of Hypothesis
Non-parametric Test Parametric univariate Multivariate
• Sign test, Wilcoxen Chi 2 t Manova
• Median test r F Canonical
• Mann-Whitney-U test R Cluster
• Kruskal -Wallis-ANOVA β Discriminate Functions
• Friedman’s ANOVA Factor Analysis
• Kendall’s coefficient Structural Equation
Modeling
 Spearman’s rank correlation
D. Post-hoc tests: individual
comparisons, Range statistics, simple
effects e.g.; Duncan’s test , Newman
Keul’s test.
E. Interpretation: Making a Statement
Type –IV errors
Thank You

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Overview of Quantitative research by Prof Rajbir Singh.

  • 1. Research Methodology Rajbir Singh, Ph.D. Professor of Psychology Maharshi Dayanand University, Rohtak
  • 2.  Functions of Research Description Explanation Prediction Control  Type of Research Context Discovery V/s Justification Pure v/s Applied
  • 3. Research : A Process  In sciences we conduct research in order to determine the acceptability of hypotheses derived from theories. Having selected a certain hypothesis which seems important in a certain theory, we collect empirical data which should yield direct information on the acceptability of that hypothesis. Our decision about the meaning of the data may lead us to retain, revise, or reject the hypothesis and even the theory which was its source.
  • 6. Sources of Data  Primary-When a researcher himself/herself observes the phenomenon and records with the help of tools or otherwise under natural or controlled conditions.  Secondary – Collecting from primary sources, e.g. census reports , remote sensing , cumulative records etc.
  • 7. Frequently Asked Questions in Research 1. When analysis? When having data/information and to draw inference 2. What type of data? Qualitative/Quantitative? 3. If qualitative what type? Narratives -Verbal Product- Non-Verbal Performance 4. If quantitative what is the Level of measurement ? Nominal, Ordinal, Interval and Ratio Scale
  • 8. 5. What Kind of Sample? Large/Small:n1, ....N=30,----N 6. How the sample has been drawn? Probability Non-probability 7. Estimation of population parameters? µ, σ 8. Verification of hypothesis, if any ? 9. Correlational/ Experimental ? 10. Parametric/Nonparametric ? 11. Univariate/bivariate/multivariate ?
  • 9. Analysis of Data A. Descriptive Presentation n=1, Xs-listing, ordering, bunching, categorization Mean, Median, Percentile, Quartile etc. Mode: Uni/bimodal/Multimodal Distribution- frequencies, class intervals SD, Range,SEM Graphic presentation- Bar diagrams, pie-charts etc. Histogram/polygon Data transformation- monotonic , uni-directional,calculative distress: √X, 1/ X,, log transformation, Arcsine transformation, X+…, X-… etc.  Normalization e.g. T-scaling (M=50,SD=10)
  • 10. B. Pre-Verification Test  Test of deviation from normality-Skewness and Kurtosis  Test of homogeneity- Bartlett's test, Cochran's test  Test of homosedacity – Range restriction-Comparing distribution  Data scanning for assumptions-  Linearity , Independence , Sphericity , Additivity etc.
  • 11. C. Verification of Hypothesis/ Goodness of fit  Statistical test yields a value that has associated probability alpha, the level of significance ( the p of making type I error, i.e.; rejecting null hypothesis when it is true). Beta, the p of type II error, accepting null hypothesis when it is in fact false. Alpha is inversely related to beta, so to reduce these errors, we must increase N.  Sample mean and SD should be equal to population parameters. Are they or are not? Sampling distribution of various statistic has p of mean and SD to approximate of µ and σ. It is the process of estimation.
  • 12. Some common Tests for verification of Hypothesis Non-parametric Test Parametric univariate Multivariate • Sign test, Wilcoxen Chi 2 t Manova • Median test r F Canonical • Mann-Whitney-U test R Cluster • Kruskal -Wallis-ANOVA β Discriminate Functions • Friedman’s ANOVA Factor Analysis • Kendall’s coefficient Structural Equation Modeling  Spearman’s rank correlation
  • 13. D. Post-hoc tests: individual comparisons, Range statistics, simple effects e.g.; Duncan’s test , Newman Keul’s test. E. Interpretation: Making a Statement Type –IV errors