1. General introduction
2. Presentation of data. 2.1 Introduction, 2.2 Types of data, tabulation of data, frequency
and frequency distribution, construction of frequency distribution table
3. Graphical Representation 3.1 Introduction of graph, types of graphs
4. Measures of Central Tendency
5. Measures of Dispersion 5.1 Introduction, different types of dispersion
6. Moments, Skewness and Kurtosis 6.1 Introduction, Definition and types of Skewness
and Kurtosis, Absolute and relative measures of Skewness, Measures of Kurtosis, Use of
Moments in Skewness and Kurtosis
7. Correlation and Regression 7.1 Correlation: Coefficient of correlation, Simple
correlation, Rank correlation, Coefficient of determination 7.2 Regression: Regression
coefficient, Simple regression, Multiple regression, Polynomial Regression 7.3 Use of
regression and correlation analysis: Limitations and Errors
8. Probability Distribution 8.1 Basic concept of probability, Related mathematics,
Elementary Probability and Conditional probability 8.2 Probability distribution, Random
variable & Expected value in Decision making8.3 Properties, constants and significance
of Binomial distribution, Poisson distribution and Normal distribution 9. Sampling 9.1 Introduction to sampling, population and sample, types of sampling-
Judgment sampling and Probability sampling 9.2 Random sampling: simple random
sampling, stratified random sampling, systematic sampling and there uses, Sample
estimates and its variances, Standard errors, Sampling and non-sampling errors
10. Basic ideas of test 10.1 Introduction: hypothesis, null hypothesis, alternative
hypothesis, label of significance, confidence limit 10.2 ‘t’ distribution, properties of ‘t’
distribution application of ‘t’ distribution, ‘t’ tests 10.3 The χ2 distribution, constants of
χ2 distribution, χ2 test, conditions for applying χ2 tests, uses of χ2 tests 10.4 The F
distribution, some special characteristics of F distribution, application of F tests,
Analysis of variance, Assumption of analysis of variance, techniques of analysis of
variance, techniques of analysis of variance one way and two way classification models
for ANOVA.
11. Experimental design 11.1 Introduction, Phases of experimental design 11.2
Randomized block design 11.3 The Latin squire design
12. Test of significance 12.1 Introduction, hypothesis, null hypothesis, alternate
hypothesis, level of significance, one tailed and two tailed test, power of a test,
construction of confidence intervals. 12.2 Special applications: Tests about means,
proportions & correlation coefficient, Test of goodness of fit, independence &
homogeneity, Test in regression analysis
13. Non parametric tests: Introduction, advantage of non-parametric tests, rank sum test,
MannWhitney test, Spearman’s rank Correlation, Kolmogorov-Smirnov sample test,
Wilcoxon Signed Rank test
14. Time series and forecasting 14.1 Introduction, utility and components of time series
analysis, measurements of trends, Graphic method, methods of semi averages, methods
of moving averages, the methods of least squires, second degree parabola, exponential
trends, growth curves, measurement of seasonal variations.