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
Location
Online via MS Teams
Teaching Assistants
Arun Verma
Fehmina Malik
Debamita Ghosh
Sayan Chatterjee
Harshit Pandey
TA Hours
Timings: Every Monday 2-4pm
Venue : Virtual meetings on request
Syllabus
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.
Course Grades (to revise)
25 points: Midterm
40 points: 4 Assingments
35 points: Endterm
Reference texts
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
Tutorials
Tutorial 1
Tutorial 2
Tutorial 3
Tutorial 4
Tutorial 5