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
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