Course

Unit 1

Quantitative methods: Basic terminology in probability, probability rules, conditions of statistical dependence and independence, Bayes Theorem, Discrete Random Variables review of probability distributions, measure of central tendency.

Sampling and sampling distributions: Introduction to sampling, random sampling, design of experiments, introduction to sampling distributions

Estimation: point estimates, interval estimates and confidence intervals, calculating interval estimates of mean from large samples, using t test, sample size estimation.

Unit 2

Testing hypothesis: Introduction, basic concepts, testing hypothesis, testing when population standard deviation is known and not known, two sample tests.

Chi-square and analysis of variance: introduction, goodness of fit, analysis of variance, inferences about a population variation

Unit 3

Regression and correlation: Estimation using regression line, correlation analysis, finding multiple regression equation, modelling techniques,

Non parametric methods and time series and forecasting: Sign test for paired data, rank sum test, rank correlation, Kolmogrov – smirnov test, variations in time series, trend analysis, cyclic variation, seasonal variation and irregular variation. Decision theory: Decision tree analysis

Course Objective

To impart the knowledge of basic statistical tools for analysis and interpretation of qualitative and quantitative data for decision making

Course Outcomes 

CO1:  Apply basic probability and statistics concepts for various business problems

CO2: Perform test of hypothesis

CO3:  Compute and interpret the result of regression and correlation analysis for forecasting

CO4:   Solve real time problems by applying different decision making methods.

CO/PO Mapping 

Evaluation Pattern

*CA – Can be Quizzes, Assignments, Projects, and Reports

TEXT BOOKS

1. Levin I. and Rubin D. S. – ‘Statistics for management’ – Pearson Education – 2007 – 5^th Edition
2. Montgomery C. and Runger G. C. – ‘Applied Statistics and Probability for Engineers’ – John Wiley & Sons – 2002 – 3^rd Edition 

REFERENCE BOOKS

1. L. J. and Engelhardt M. – ‘Introduction to Probability and Mathematical Statistics’ – Duxbury Press –
   March 2000 – 2^nd Edition

2. Hinkelmann and Kempthorne O. – ‘Design and Analysis of Experiments : Volume I’ – John Wiley & Sons, Inc. – December 2007 – 2^nd Edition
3. Johnson A. and Wichern D. W. – ‘Applied Multivariate Statistical Analysis’ – Prentice-Hall, Inc. – December 2001 – 5^th Edition
4. Myers H. – ‘Classical and Modern Regression with Applications’ – PWS-Kent Publishing Company – March 2000 – 2^nd Edition
5. Devore L. – ‘Probability and Statistics for Engineering and the Sciences’ – Brooks/Cole Publishing Company – December 1999 – 5^th Edition
6. Freund E. and Walpole R. E. – ‘Mathematical Statistics’ – Prentice-Hall Inc. – October 1986 – 4^th Edition