Lecture | Date | Topic(s) | Data/Assignment | Reading | Computer Program |
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1a,b,c | 1/12 | Introduction; Review of simple and multiple regression; Matrix and SAS/IML review; Review of statistical inference for regression |
Short answers
due lecture 2 Hw1, due lecture 4 Some Hw1 hints |
Chapters 5-6 | Davis.txt prestige.txt Davis SAS program Davis SAS output R Davis code Prestige SAS program Prestige SAS output R Prestige code IML intro IML SAS output R Matrix code |
2 | 1/17 | Review of statistical inference for regression; ANCOVA, the principle of marginality |
Chapters 6-7 | Drop test SAS Program
Ancova SAS program Ancova SAS output SAS-text comparison R Ancova code |
|
3a,b,c | 1/19 | ANCOVA, the principle of marginality; Analysis of variance |
Chapter 7-8 | Moore.txt Anova SAS program Anova SAS output R Anova code |
|
4a,b,c | 1/24 | ANOVA; Statistical theory for linear models | Hw1 due |
Chap. 9.1-9.2 | |
5a,b,c | 1/26 | Statistical theory for linear models | Hw2, due lecture 8 | Chap. 9.1-9.2 | |
6a,b | 1/31 | Homework 1 review; More statistical theory for linear models; Properties of the least-squares estimator |
Chap. 9.3-9.4 | ||
7 | 2/2 | Properties of the least-squares estimator; Inference for several coefficients |
Some Hw2 hints | Chap. 9.3-9.4 | Gen Lin Hyp SAS code; GLH SAS output R GLH code |
8a, b | 2/7 | Inference
for coefficients; Joint Confidence Regions; Random regressors; Specification error; Confidence and prediction intervals |
|
Chap. 9.4 -9.7 | Joint Conf. Ellipse 1; Joint Conf. Ellipse 2; Crime data info; Crime data; R Conf. Ellipse code |
9a,b | 2/9 | Vector Geometry of Linear Models | Hw2
due; Exam 1 takehome; Concrete data |
Chap. 10.1-10.4 |
Geometry R code Geometry SAS code; Geom. SAS Fig1 ; Geom. SAS Fig2 ; LS Geometry figure |
10 | 2/14 | Homework 2 review; Vector Geometry of Linear Models |
Chap. 10.1-10.4 | Anova R code Anova Geometry SAS code ; Anova SAS 1; Anova SAS 2 |
|
11a,b,c | 2/16 | Vector Geometry of Linear
Models; Statistical theory for linear models; Theory about TSS decomposition |
Chap. 10 and extra |
Quadratic form SAS code | |
12 | 2/21 | Exam 1 | |||
13a,b | 2/23 Note alternate location!! |
Hat values and residuals; Measuring Influence |
Hw3, due lecture 16 | Chap. 11-1-11.5 | Duncan.txt; Hat, resid SAS program; Hat, resid SAS output; R Hat, resid code |
14 | 2/28 | Exam 1 Review; Joint Influence | Chap. 11.6-11.8 | Partial Reg. SAS code; Partial Reg. SAS output; R Partial Reg. code; R Forward Search code; R Forward Search Figure |
|
15a, b | 3/2 | The normality assumption; The constant variance assumption |
Chap. 12.1-12.2 | SLID1.txt; Quantile/KDE SAS program; Quantile/KDE SAS output; R quantile/KDE code; WLS SAS code; WLS SAS output; R WLS code; Sandwich SAS code; Sandwich SAS output; R Sandwich code |
|
16a,b,c,d | 3/7 | The linearity assumption; Discrete data; Box-Cox transformations |
Hw3 due | Chap. 12.2-12.6 | Part. resid. example SAS; Part. resid SAS output; SLID part.res. SAS code; SLID part. res. output; R part. res. code; Vocabulary.txt; discrete data SAS code; discrete data SAS output; R discrete data code; Box-Cox SAS code; Box-Cox output; R Box-Cox code |
17a,b,c,d | 3/9 | Box-Tidwell transformations; More tests for constant variance; Structural Dimension; Detecting Collinearity |
Hw4, due lecture 20 | Chap. 12.5-12.6; Chap. 13.1-2 |
Box-Tidwell SAS code;
Box-Tidwell output; R Box-Tidwell code; BFox.txt; Collinearity SAS code; Collinearity output; R Collinearity code |
3/13-3/17 | Spring break - no classes | ||||
18a,b,c | 3/21 | Hw3 review; Detecting Collinearity; Model Respecification; Variable Selection; |
Chap. 13.1-2 | Model selection SAS code; Model selection output; R Model selection code; |
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19a,b | 3/23 | Variable Selection Methods | Chap. 13.1-2 | Ridge regr. SAS code; Ridge regression output; R Ridge reg. code; ESL example SAS code; ESL data |
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20 | 3/28 | Nonlinear Regression | Chap. 17.4 | Nonlinear regr. SAS code; Nonlinear regr. output; R Nonlinear code |
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21 | 3/30 | Models for Dichotomous Data | Hw4 due; Exam 2 take-home |
Chap. 14.1 | Cereals.txt; Simple Logistic Reg.code; SAS Logistic Reg output; R Logistic Reg. code |
22 a,b | 4/4 | Homework 4 Review; Models for Dichotomous Data |
Chap. 14.1 | SLID-women.txt; Logistic Reg. SAS code; Logistic Reg. SAS output; R Logistic Reg. code |
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23 | 4/6 | The Structure of Generalized Linear Models | Chap. 15.1-1 | SAS Deviance calculation; SAS Dev. Calc. output |
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24 | 4/11 | Exam 2 | |||
25 | 4/13 | The
Structure of Generalized Linear Models; GLMs for Count Data |
Chap. 15.1-2 | Ornstein.txt; Poisson Reg. SAS code; Poisson Reg. output ; R Poisson Reg. code ; IWLS SAS code; IWLS SAS output |
|
26 a,b | 4/18 | Exam 2 Review; Statistical Theory for Generalized Linear Models |
Hw5, for review | Chap. 15.3 | |
27 | 4/20 | Diagnostics for Generalized Linear Models | Chap. 15.3-4 | Deviance calculation SAS code; Deviance output; GLM Diag. SAS code; GLM Diag. output; R GLM Diag. code |
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28 | 4/25 | Introduction to Mixed Models | Mixed SAS code; Mixed SAS output; R Mixed code |
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29 | 4/27 | Mixed Models | Exam 3 take home; Seattle; Oakland; Texas; Alaska |
Chap. 23.1-6 | SAS School code; SAS Eating code; R Eating code |
30 | 5/2 | Student talks | |||
31 | 5/4 | Homework 5 review | |||
Finals week |
Office hours: M 9:30-12 |
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Finals week |
Exam on Monday, May 8 at 12:30 pm |
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