Course: Mathematical Statistics

This course provides an elementary introduction to mathematical statistics with applications. Topics include: statistical estimation, hypothesis testing; confidence intervals; calculation of a P-value; nonparametric testing; curve fitting; analysis of variance and factorial experimental design.
Students at the end of course should be able to do the following:
1) Understand the concepts and methods of statistics inference
2) Contrast, evaluate, and implement element sampling designs
3) Understand statistics as a comprehensive approach to data analysis
4) Utilize Minitab program for analyzing data and summarizing

Syllabus

Prerequisite: one year course in calculus; Probability Theory
Textbooks (required):
Miller & Freund's Probability and Statistics for Engineers (Seventh Edition), Richard A. Johnson. Publishing House of Electronics Industry or Pearson Education Press. Chapter 7 -- Chapter 13.
References:
1) A First course in Probability (6th Ed), Sheldon Ross. China Statistics Press.
2) Probability & Statistics for Engineers & Scientists (7th Ed), R.E. Walpole,R.H. Myers, S.L. Myers, K. Ye. Tshinghua or Pearson Education Press.
Week schedule (may update later)

Course policies

Grading: Grades for the course will be based on the following weighting
1) Class attendance: 10%
2) Homework assignment+QUIZ: 50%
3) Final exam: 40%
Homework:
1) We may collaborate on homework, but you must write your submitted work in your own words. This includes showing calculations, derivations, and proofs. Solutions will be posted on the class web site.
2)Assignments are due in class as noted in the syllabus and web page. Homework assignments turned in within 48 hours of the due dates will be penalized 20% even if the solutions are "correct". HW more than two days late may not get graded at all.