# 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   Job 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. 7 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