Lecture 5: General Linear Test
& Descriptive Measures
STAT 512
Spring 2011
Background Reading
KNNL: 2.8 2.9
5-1
General Linear Test
Different view of testing H0: 1 0
Compare two models:
Yi 0 1 X i i
(full model)
Yi 0 i (reduced model)
F-statistic can b
Lecture 4: ANOVA Table
STAT 512
Spring 2011
Background Reading
KNNL: 2.6-2.7
4-1
Topic Overview
Working-Hotelling Confidence Band
Inference Example using SAS
ANOVA Table
4-2
Working-Hotelling
Confidence Band (1)
This gives a confidence limit for the w
Lecture 6
Regression Diagnostics
STAT 512
Spring 2011
Background Reading
KNNL: 3.1-3.6
6-1
Topic Overview
Chapter 3 Diagnostics & Remedial Measures
for Simple Linear Regression
Diagnostics: Look at the data to diagnose
situations where the assumptions of
Lecture 3: Inference in SLR
STAT 512
Spring 2011
Background Reading
KNNL: 2.1 2.6
3-1
Topic Overview
This topic will cover:
Review of hypothesis testing
Inference about 1
Inference about 0
Confidence Intervals
Prediction Intervals
3-2
Review: Signifi
Lecture 11
Multiple Linear Regression
STAT 512
Spring 2011
Background Reading
KNNL: 6.1-6.5
11-1
Topic Overview
Review: Multiple Linear Regression (MLR)
Computer Science Case Study
11-2
Multiple Regression Model
Y X
n1
np p1
n1
2
where ~ N 0, I
nn
X i
Lecture 13
Extra Sums of Squares
STAT 512
Spring 2011
Background Reading
KNNL: 7.1-7.4
13-1
Topic Overview
Extra Sums of Squares (Defined)
2
2
Using and Interpreting R and Partial-R
Getting ESS and Partial-R2 from SAS
General Linear Test (Review Section 2
Lecture 2
Simple Linear Regression
STAT 512
Spring 2011
Background Reading
KNNL: Chapter 1
2-1
Topic Overview
This topic we will cover:
Regression Terminology
Simple Linear Regression with a single
predictor variable
2-2
Relationships Among Variables
F
Lecture 10
Multiple Linear Regression
STAT 512
Spring 2011
Background Reading
KNNL: 6.1-6.5
10-1
Topic Overview
Multiple Linear Regression Model
10-2
Data for Multiple Regression
Yi is the response variable (as usual)
X i 1, Xi 2, Xi,p1 are the p 1 exp
Lecture 8
Matrix Review
STAT 512
Spring 2011
Background Reading
KNNL: Chapter 5
8-1
Topic Overview
Review: Matrix Algebra
Matrix Notation
8-2
Matrices
We will utilize matrices to simply the
regression model.
This is particularly important so that when
Lecture 9
SLR in Matrix Form
STAT 512
Spring 2011
Background Reading
KNNL: Chapter 5
9-1
Topic Overview
Matrix Equations for SLR
Dont focus so much on the matrix
arithmetic as on the form of the equations.
Try to understand how the different pieces
fit
STAT 512 Spring 2011
Prof. Gayla Olbricht
Lecture 1: Class Logistics/SAS
Outline
Overview
Class Information and Policies
SAS Software/Example
Background Reading
Overview
We will cover:
Simple linear regression (SLR) Chapters 1-5
Multiple linear regression