Part 1: "Causal" Models:  Using X to forecast, explain, control Y

1 6/8
Ch. 1

Ch. 3

Chapter 1: Introduction to Forecasting
Case: Forecasting With Regression Analysis p. 1-7
3.1-3.4 Simple Linear Regression      
The Sums of Squares  

J
ob Satisfaction Data    Satisfaction versus Education
Fuel Consumption: Fahrenheit and Celsius
(no homwork due)
2 6/10
Ch . 3 5-8 Simple Linear Regression: Tests and Interval Estimates
Case: Forecasting With Regression Analysis p, 10-15
    House Price spreadsheet
Assignment 1 Due
Point Estimates
EmployeeData.xls
Jobsat-Educat.pdf
3
6/15
Ch. 2 Statistics:  Online Class
Examples
(no homwork due)
4
6/17
/Ch. 2
Data Cleaning: Online Class
Leusire Research Methods  (C. Hammersly)
Data Cleaning and Verification (J. Holcomb)
             Solution for alkaline phosphates   
(no homwork due)
5
6/22
Ch. 3 Review Chapters 1, 2, 3
Data Cleaning and Verification (J. Holcomb)
             Solution for alkaline phosphates  
Assignment 2 Due
Statistics
6
6/24 Ch. 4
pt. 1

4.1 The Multiple Linear Regression Model 140         Houses        Fuel
4.2  Least Squares Estimates, Point Estimation & Prediction 148
4.3 The Mean Square Error and the Standard Error 154
4.4 Model Utility: R2, Adjusted R2, and the Overall F-Test 155
Case: Forecasting With Regression Analysis p. 7-10
Assignment 3 Due
Data Cleaning
 
Teams allowed.


6/29
Ch. 4
pt. 2
4.5 Testing Significance of an Independent Variable 160
4.6 Confidence and Prediction Intervals 163
4.7 The Quadratic Regression Model 167
Fuel additive    Detergent        Pies
Assignment 4 Due
Interval Estimates
for Parameters
8 7/1 Ch. 4
pt.3

4.8  Interaction    175      Barbituates     Poison     Flowers
4.9 Dummy Variables to Model Qualitative Independent Var. 183
4.10 The Partial F-Test: Testing part of a Regression Model 193
Case: Forecasting With Regression Analysis p. 15-19
Assignmentt 5 Due
Point Estimates From
Multiple Regression
 sat-es-sal.xls

7/6

Independence Day Holiday
(no homwork due)
9 7/8 Ch. 5 5.1 Model Building and Multicolinearity
      Multicollinearity    Good & Bad variables    
     Comparing Regression Models
     Stepwise Regression      Backward Elimination
Forecasting With Regression Analysis p.7-10: Proxy Effect
Assignment 6 Due
Testing Multiple
Regression
10
7/13
Ch. 5
1.3, 5.2-5.4 Residual Analysis
 Barbiturates     Pies    Population 
  Transformations  Home Maintenance
Case: Forecasting With Regression Analysis p. 15-18   
Assignment 7 Due
Multicolineary