Lesson 10: Applied Regression Analysis (2 of 2)
February 20, 2019
Review:
- Variable Selection
- Real Estate Selling Price estimates/forecasts
- Exam 2
- Part 1 – regression modeling project instructions (Mon Feb 25)
- Part 2 – in-class exam with questions about your regression model (Wed Feb 27)
Presentation:
- Applied Regression Analysis
- Dummy Variables
- incorporate categorical variables
- binary – value is either 1 or 0
- if 0, then the coefficient has no effect on y-hat
- if 1, then the coefficient is added to (or subtracted from) the estimate
- Demonstration with Sample Real Estate data
- create a dummy variable for a neighborhood
- Dummy Variables
Assignment:
- Build a regression model to estimate Real Estate selling prices
- Use this data set Pueblo RE East Side
- Create and use a dummy variable for “Belmont”
- Use your regression model to estimate selling prices for these 4 properties
- Belmont 3 BR, 2 BA, 1600 SqFt
- Belmont 4 BR, 3 BA, 2400 SqFt
- East Side 3 BR, 1 BA, 1200 SqFt
- East Side 2 BR, 1 BA, 800 SqFt
- Add results to your Portfolio
- Regression output
- y-hat equation
- 4 property Selling Price estimates