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
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Sheldon Ross, ``Introduction to Probability Models,'' (Eleventh Edition), Elsevier 2014,
Download.
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Douglas C. Montgomery, Larry Faris Thomas and George C. Runger (2003) ``Engineering Statistics, 3rd edition, John Wiley & Sons. Download.
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Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer (2007) Mathematical Statistics with Applications, 7th edition, Duxbury Resource Center.
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John A. Rice (1994) Mathematical Statistics and Data Analysis, 3rd edition, Thomson Learning Download.
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George Casella and Roger Berger (2004) Statistical Inference, 2nd edition, Thomson Learning. Download.
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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