

Lecture A (33790/37890) Mon, Wed 9:30  10:50am Lecture B (37800/37895) Mon, Wed 12:30  1:50pm 
A1: Fri 9:00  9:50; A2: Fri 10:00  10:50 B1: Fri 11:00  11:50; B2: Fri 12:00  12:50 
Professor Jessica Utts  Lecture A TA: Wendy Rummerfield  Lecture B TA: Brandon Berman 
2212 Donald Bren Hall  2032 Donald Bren Hall  2013 Donald Bren Hall 
(949) 8240649  no phone  no phone 
jutts_at_uci.edu [Not clickable to avoid spam]  wrummerf_at_uci.edu  bermanb_at_uci 
Mon, Wed 2:00 to 3:30 and by appointment  Mon 1112:30, Tues 3:305  Mon 3:305, Fri 12:30 
Mon  Tues  Wed  Thurs  Fri 
11:0012:30, Rummerfield; 2:003:30, Utts; 3:305:00, Berman Finals week (Dec 11): 11:001:00, Berman, 2032 DBH 
3:305:00, Rummerfield Finals week (Dec 12): 3:305:00, Utts, 2032 DBH  2:003:30, Utts Finals week: None  None  12:30, Berman Finals week: None 
Assignment #1, Due Wed, Oct 11 Assignment #2, Due Wed, Oct 18 Assignment #3, Due Wed, Oct 25 Assignment #4, Due Mon, Oct 30 Assignment #5, Due Wed, Nov 15 Assignment #6 for 110, Due Wed, Nov 22 Assignment #6 for 201, Due Wed, Nov 22 Assignment #7, Due Wed, Nov 29 Assignment #8, Due Wed, Dec 6
Date  Sections covered and skipped; other topics covered  Material from class lectures and discussion (posted when covered)  Assignment and Date Due  
Fri Sept 29  NO DISCUSSION SECTIONS TODAY  
Mon Oct 2  Introduction and start Chapter 0  Lecture 1 slides (as a pdf file, 6 to a page)  
Wed Oct 4  Finish Chapter 0; Sections 1.1, 1.2  Lecture 2 slides or Compact version  Homework assignment #1, due Wed, Oct 11  
Fri Oct 6 Disc  Introduction to R and R Studio  Notes for Oct 6 discussion in html, and in pdf  
Mon Oct 9  Sections 1.3 to 1.5  Lecture 3 slides or Compact version  
Wed Oct 11  Review hypothesis testing, confidence intervals and distributions; Section 2.1  Lecture 4 slides or Compact version
R code and results for Highway signreading example 
Homework assignment #2, due Wed, Oct 18  
Fri Oct 13 Disc  R for Regression (plots, linear models, etc)  Notes for Oct 13 discussion in html, and in pdf  
Mon Oct 16  Sections 2.2 and 2.3  Lecture 5 slides or Compact version
Skin cancer example  
Wed Oct 18  Confidence and prediction intervals, Section 2.4  Lecture 6 slides or Compact version
Highway sign example showing CI and PI commands and results  Homework assignment #3, due Wed, Oct 25  
Fri Oct 20 Disc  More R for Regression; Question and Answer  Notes for Oct 20 discussion in pdf  
Mon Oct 23  Sections 3.1 and 3.2  Lecture 7 slides or Compact version  
Wed Oct 25  Section 3.3 and Section 3.6 as applied to material in 3.3  Lecture 8 slides (in color) or Compact version (in black and white)  Homework assignment #4, due Mon, Oct 30 Pulse data for this assignment is part of the Stat2Data library  
Fri Oct 27 Disc  Midterm review  Review for Midterm  
Mon Oct 30  Section 3.5; More about ANOVA (not in book)  No lecture slides today  on white board, and these 2 examples:
Multicollinearity example and Example of why order matters  
Wed Nov 1  MIDTERM EXAM (covers through Fri, Oct 27)  No homework this week  
Fri Nov 3 Disc  More about R for multiple regression 
Notes for Nov 3 discussion in html, and in pdf Salary data  
Mon Nov 6  Section 3.4 and finish Section 3.6  Lecture 11 slides in color or in black and white or Compact version  Homework assignment #5, due Wed, Nov 15 (covers 10/30 and 11/6 lectures)
Exercises 3.23 to 3.26 from book (in case you don't have the book)  
Wed Nov 8  Section 4.2 (Skip 4.1)  Lecture 12 slides or Compact version Best Subsets Real Estate Example  
Fri Nov 10 Disc  Veterans' Day Holiday  no class  
Mon Nov 13  Sections 1.5 and 4.3  Finish Lecture 12 first. Lecture 13 slides or Compact version Case diagnostics for the real estate example Case diagnostics in R 
Homework assignment #6 for Stat 110 students only; Hmwk6 data for Stat 110 as txt file or as Excel file Homework assignment #6 for Stat 201 students only; StateSAT data for Stat 201 as txt file or as Excel file Description of State SAT data Both due Wed, Nov 22 (covers 11/8 and 11/13 lectures)  
Wed Nov 15  R for creating and comparing models; variable selection methods in R  R code for Nov 15 lecture in html, and in pdf
County Demographic Information (CDI) data  
Fri Nov 17 Disc  Case diagnostics in R; Regression hypotheses stated as models  Notes for Nov 17 discussion, pdf only  
Mon Nov 20  Start Chapter 5  Lecture 15 slides or Compact version
GPA and seat location example Party Days and seat location example  
Wed Nov 22  Continue Chapter 5; Section 7.2  Lecture 16 outline (Lecture on the white board)
Party Days and seat location example (Continued from last time)  Homework assignment #7, due Wed, Nov 29  
Fri Nov 24  Thanksgiving Holiday  no class  
Mon Nov 27  Chapter 6  Lecture 17 slides or Compact version Two factor ANOVA Example  
Wed Nov 29  Other topics in analysis of variance (unbalanced twofactor, random effects, nested factors, repeated measures)  Lecture 18 slides or Compact version ANOVA scenarios for discussion and Answers (posted after class)  Homework assignment #8, due Dec 6  
Fri Dec 1 Disc  R for analysis of variance; comparing lm, anova and aov  Notes for Dec 1 discussion, pdf only  
Mon Dec 4  Sections 4.4, 7.5 and 7.6 (Analysis of covariance)  Lecture 19 outline; Lecture will be on white board
Analysis of covariance example 

Wed Dec 6  Analysis of variance with more than two factors; Review for final exam  Review for final exam  
Fri Dec 8 Disc  Final exam review, questions and answers  
Mon Dec 11  Lecture B Final Exam, 1:30 to 3:30pm  
Wed Dec 13  Lecture A Final Exam, 8:00 to 10:00am 