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 9:0010:45am and Wednesdays 12:301:45pm @ DBH 2032
Reader: Shengni Wang, shengnw@uci.eud, office hour: Friday 1:302:45pm
Lecture notes:
Please review the hypothesis testing note that I used for stat120B
· T tests: one sample ttest, two sample ttest, 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
Description and
Objectives
Stat 120C is the last of a threequarter 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, 3^{rd} edition. Duxbury.
Typos: http://www.stat.berkeley.edu/users/rice/Book3ed/index.html
Two other references:
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.rproject.org.
Grading
The grade is based upon seveneight 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, 10:30am12:30pm at SSPA 1100.
Both the midterm and the final are closedbook and inclass. 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 712, 3032, 42 of An Introduction to R,
9.1, 9.4, 9.5 of Rice, p426428 of Rice 
Weeks
3,4: 
Oneway
ANOVA 
P477489
of Rice 
Week
5: 
twoway
ANOVA 
P489499
of Rice 
Week
6: 
simple
linear regression midterm 
P542563
of Rice 
Week
7: 
multiple linear regression, contingency
table and Fisher’s exact test 
P564580
of Rice, P514516
of Rice 
Week
8: 
test
of homogeneity, test
of independence 
P516520
of Rice, P520523
of Rice 
Week
9: 
matched
pairs and measures of association 
P523530
of Rice 
Week
10: 
nonparametric tests 
P435443, 448451, 488489 of Rice 