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Course Overview

M&M 2.1-2.5, 6.1-6.3, also p. 657-670

Lab: Intro to Splus, commands for HW1, #4.

Simple linear regression example

Homework 1 due January 20^th in class

2

1/13

1/15

Simple Linear Regression

CI for mean, prediction intervals

Ch. 1, 7.1-7.4 of Sleuth.

Sleuth 7.5-7.6; M&M p. 671-675

Lab Agenda

List of supplementary readings, inference in linear regression

Example: Elemental carbon and diesel exhaust

Derivation of SD of the mean response and link with centering trick

3

1/20

1/22

Robustness, model checking, log transforms

Sleuth 8.1-8.4

Lab Agenda

Handed out: Display 3.8 from Sleuth, Review of "A Life of Sir Francis Galton" (NYT, 2/10/02)

Lecture outline for Ch. 7, 8: R2,CI for mean response,prediction intervals, inverse regression, log transformations of data.

Plots for Case Study 8.1.1, number of species and island area.

How to interpret the slope for Case 8.1.1, a log-log model

Overview of multiple comparison procedures.

(Homework 1 turned in 1/20)

Homework 2, due January 28^th in lab

4

1/27

1/29

Log transforms

ANOVA tables for regression

Lack of fit test

Sleuth

8.4-8.6

Lab Agenda

Lecture notes: log transforms, lack of fit test

Practice problems for Chapter 8

(HW2 turned in 1/28)

5

2/3

2/5

Chapter 7, 8 overview

Addendum to previous lecture notes, Course outline through Chapter 8

For lab handouts, go to "Course Documents" - "Lab Handouts" in Blackboard

MIDTERM 1, Thursday, 2/5 in class

Meat processing example, 2 handouts

6

2/10

2/12

Multiple regression

Sleuth,

Ch. 9

M&M 11.1

Handout on Case 9.1.2, Mammals and Brain Size (multiple regression) and on damage to spruce trees as a function of elevation in the North and South (use of a 2-level indicator variable)
Lab Agenda: Meadowfoam Example

HW3, due 2/19 at 5pm to McBride mailbox in LSRC mailroom

7

2/17

2/19

Inferential tools for multiple regression

Sleuth, Ch. 10

Handout: logit/arcsinsqrt transforms for proportions; more details on spruce example (ANOVA tables for regression, ESS F-tests); polynomial regression
Handout: Bat Echolocation Example Case 10.1.2

HW4, due Friday at noon, 2/27.

Week

Date

Topics

Reading

Handouts

Due Dates

8

2/24

2/26

Model Checking, Refinement

Sleuth, Ch. 11

9

3/2

3/4

Measures of influence in regression

Sleuth, Ch. 11

• Chapter 11 lecture outline, continued

• Presentation of Ch. 11 material by Dan Shafer, Oregon State, page 9 on

• Derivation of variance of a residual (for the energetic student)

MIDTERM 2, Thursday, 3/4 in class

10

3/9

3/11

Spring Break

11

3/16

3/18

Strategies for Variable Selection

Sleuth, Ch. 12

Lab Agenda: Splus implementation of Chapter 11 topics

TAKE-HOME MIDTERM, assigned 3/16 due 3/23

12

3/23

3/25

Model Selection

Chapter 12

Lab Agenda: Work through the Gender Discrimination example using all subsets model selection and Bayesian analysis

Project Presentation Info: Project Proposal Due Monday 3/29 5pm.

13

3/30

4/1

Comparisons of proportions or odds; tools for tables of counts; Logistic Regression for Binary Response

MP Presentations 4/1: No class

Read Chapter 18, p. 529-535; Skim 18.2.2, 18.2.3; Read 18.3 on odds ratios; Skim 18.3.4; Read 18.4; Read Chapter 20. M&M: p 367-top p 373; Chapter 15 on logistic regression, available under course documents.

HW5: due April 8

14

4/6

4/8

Logistic Regression for Binary Response and for Binomial Counts

Sleuth Ch 20, 21

15

4/13

4/15

Log-linear regression for poisson counts

Sleuth Ch 22

Final project presentations

16

4/20

4/22

Reading Week

17

Week of 4/26

Final Exam