STAT 120C / 281C: Introduction to Probability and Statistics III

 

 

Meeting Information

Room: SSPA 1100

Day & time: M W F 08:00am to 8:50am

Instructor Information

Zhaoxia Yu

Email: zhaoxia@ics.uci.edu

Office Location: 2214 Bren Hall

Office hour: 9am every Thursday or by appointment

TA: Wendy Rummerfield, wrummerf@uci.edu, office hour: Tuesdays 9:00-10:45am and Wednesdays 12:30-1:45pm @ DBH 2032

Reader: Shengni Wang, shengnw@uci.eud, office hour: Friday 1:30-2:45pm

Academic Honesty policies

 

 

Lecture notes:

Please review the hypothesis testing note that I used for stat120B

 

·        T tests: one sample t-test, two sample t-test, LRT (in class note), LRT for the two sample problem (with all the details you need)

 

·        ANOVA: a numerical example, part 1, part 2, part 3, part 4, part 5, part 6

 

·        Linear regression: part 1, part 2, part 3

o   in class notes: April 13, April 16, April 20, April 23, April 25, April 27, April 30, May 1 Discussion (R code, Data), May 2, May 4

 

·        linear models: May 9, May 11, May 14, May 16

o   Multiple linear regression (LSE and MLE)

 

·        categorical analysis: slides

 

·        Nonparametric methods: slides

 

·        Final review: slides

 

Discussions:

Homework assignments: homework1, homework 2, homework 3, homework 4, homework 5 , homework 6, homework 7 (this homework won’t be collected or graded)

 

Handouts: handout1 (R code), handout2 (R code), handout3 (R code), handout4 (R code)

Practice exams: practice midterm (solution), practice final

 

R resources

 

Description and Objectives

Stat 120C is the last of a three-quarter series on introduction to probability and statistics.

The goal of this course is to introduce basic principles of probability and statistical inference. Topics that will be covered include linear regression, analysis of variance, and categorical analysis.

 

 

The following book is highly recommended:

Rice, J. (2006). Mathematical Statistics and Data Analysis, 3rd edition. Duxbury.

Typos: http://www.stat.berkeley.edu/users/rice/Book3ed/index.html

 

Two other references:

  1. DeGroot, MH. and Schervish, MJ. (2002) Probability and Statistics, 3rd edition. Addison Wesley.
  2. Neter, J., Kutner, MH., Nachtsheim, CJ., and Wasserman, W. (2005). Applied linear statistical models, 5th edition. McGraw-Hill Irwin.

 

Software/Computing:

The statistical package R will be used to illustrate examples. R is a free package that can be installed onto machines with different operation systems. For more information about R, please visit http://www.r-project.org.

 

Grading

The grade is based upon seven-eight homework assignments (20%), a midterm (30%) and a final exam (50%). No late homework will be accepted.

 

Important Dates

Midterm: Monday, May 7

Final: Thu, 6/14, 10:30am-12:30pm at SSPA 1100.

Both the midterm and the final are closed-book and in-class. One or two pages of notes will be allowed. The final exam will cover the material presented in 120C.

 

Prerequisites

Statistics 120B, or equivalent, or permission from instructor.

 

Tentative course schedule and reading assignments

 

Topic

Reading assignment

Weeks 1,2:

Introduction and review,

Equivalence between 2 sample t and LRT

Ch6, 9 of Rice, Pages 7-12, 30-32, 42 of An Introduction to R, 9.1, 9.4, 9.5 of Rice, p426-428 of Rice

Weeks 3,4:

One-way ANOVA

P477-489 of Rice

Week 5:

two-way ANOVA

P489-499 of Rice

Week 6:

simple linear regression

midterm

P542-563 of Rice

Week 7:

multiple linear regression,

contingency table and Fisher’s exact test

P564-580 of Rice,

P514-516 of Rice

Week 8:

test of homogeneity,

test of independence

P516-520 of Rice,

P520-523 of Rice

Week 9:

matched pairs and measures of association

P523-530 of Rice

Week 10:

nonparametric tests

P435-443, 448-451, 488-489 of Rice