INFORMATION SHEET

Basic concepts and Data Visualization: Measures of central tendency, Dispersion, Skewness, Kurtosis, Data Representation using Histogram, Pie Chart, Boxplot, Biplot, multi-dimensional Scaling etc.;

Revision of Probability Distribution: Emphasis on Normal, Chi-Square, Student’s T, F distributions;

Order Statistics: Different Order Statistics and their single and joint Distribution;

Sampling Distribution of Mean, Variance;

Random Number Generation: Generation of Random Numbers following certain distributions;

Theory of Estimation (Point and Interval) Properties of an estimator, MVUE, BLUE, Cramer-Rao Inequality, Rao-Blackwell Theorem;

Testing of Hypothesis: Mean and Variance, Confidence Interval, Neyman-Pearson Lemma; Non-Parametric Methods Run Tests, Rank Tests, Signed Rank Tests, Kruskal Wallis Test, Kolmogorov-Smirnov Test etc.;

Regression Analysis Linear Regression, Multiple Regression, Logit, Probit, Regression;

Time Series Analysis: Time Series Decomposition, Smoothing and Moving Averages, ARIMA Models;

(No. of Lectures - 42)

Main Text Books

1.      Introduction to Statistical Methods, Design of Experiments and Statistical Quality Control, Selvamuthu Dharmaraja, Dipayan Das, Springer, 2018.

2.      Vijay K. Rohatgi and A.K. Md. Ehsanes Saleh, Dasgupta, An Introduction to Probability and Statistics, John Wiley, edition, 3rd edition, 2015.

Reference Books

1.      Rudolf J. Freund, Donna Mohr and William J. Wilson, Statistical Methods, Academic Press, 3^rd edition, 2010.

2.      Anthony Hayter, Probability and Statistics for Engineers, Cengage, Learning, 4^th edition

3.      A. M. Gun, M. K. Gupta B. Dasgupta, Fundamentals of Statistics, Vol. 1, World Press, 2008.

4.      Sheldon Ross, Introduction to Probability and Statistics for Engineers and Scientists, 5th Edition, Academic Press, 2014.