Class Time| |
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| 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) 824-0649 | 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 11-12:30, Tues 3:30-5 | Mon 3:30-5, Fri 1-2:30 |
| Mon | Tues | Wed | Thurs | Fri |
| 11:00-12:30, Rummerfield; 2:00-3:30, Utts; 3:30-5:00, Berman Finals week (Dec 11): 11:00-1:00, Berman, 2032 DBH |
3:30-5:00, Rummerfield Finals week (Dec 12): 3:30-5:00, Utts, 2032 DBH | 2:00-3:30, Utts Finals week: None | None | 1-2:30, Berman Finals week: None |
Syllabus and other informationInformation about getting an ICS Computing Account, and Installing and Using R and R Studio (Updated throughout the quarter)Data Sets and Applets that will be used in the course (additional ones posted as needed)Practice Exams and Exam KeysHomework Solutions, posted after they are due 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
Daily Schedule| 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 sign-reading 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 two-factor, 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 |
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| 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 |
