IE605: Engineering Statistics, Aug-Nov 2020

The course provides a strong foundation in theory and methods of modeling randomness and data analysis in engineering applications.

Lecture Hours

Monday 8.30-9.30am
Tuesday 9.30-10.30am
Thursday 10.30am-11.30am

Online via MS Teams

Arun Verma
Fehmina Malik
Debamita Ghosh
Sayan Chatterjee
Harshit Pandey

Timings: Every Monday 2-4pm
Venue : Virtual meetings on request

Review of calculus-based probability concepts, common distributions, expectation, moment generating functions

Sampling statistics, order statistics, properties of sample mean, Central Limit Theorem. Sampling from a Normal distribution

Parameter estimation, maximum likelihood estimators, interval estimates; bias, efficiency and consistency of point estimators

Sampling plans, sequential tests, Hypothesis testing, common tests concerning means, variances

Goodness-of-fit, likelihood ratio test, Neyman-Pearson lemma; Regression models, design of experiments.

25 points: Midterm
40 points: 4 Assingments
35 points: Endterm

Sheldon Ross, ``Introduction to Probability Models,'' (Eleventh Edition), Elsevier 2014, Download.

Douglas C. Montgomery, Larry Faris Thomas and George C. Runger (2003) ``Engineering Statistics, 3rd edition, John Wiley & Sons. Download.

Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer (2007) Mathematical Statistics with Applications, 7th edition, Duxbury Resource Center.

John A. Rice (1994) Mathematical Statistics and Data Analysis, 3rd edition, Thomson Learning Download.

George Casella and Roger Berger (2004) Statistical Inference, 2nd edition, Thomson Learning. Download.

Ajit C. Tamhane and Dorothy D. Dunlop (1999) Statistics and Data Analysis: From Elementary to Intermediate, Prentice Hall

Tutorial 1

Tutorial 2

Tutorial 3

Tutorial 4

Tutorial 5