1. 1 BA 275 Quantitative Business Methods Please turn in Progress Report #2 Quiz # 5 Simple Linear Regression Introduction Case Study: Housing Prices Agenda

2. 2 Midterm Examination #2 Monday, February 26, 2007 in class for 110 minutes. It covers materials assigned in Week 4 – 7. Need a calculator and a good night sleep. Close book/note/friends except for a 4” x 6” index card. I will provide you 1. the normal probability table. 2. Table D A 4” x 6” index card is allowed. Write your name and section number on top and turn it in with your exam. Office Hours: Friday, 2/23/2007, 3:10 – 5:00 p.m. Monday, 2/26/2007, 8:30 – 11:00 a.m.

3. 3 Regression Analysis A technique to examine the relationship between an outcome variable (dependent variable, Y) and an explanatory variable (independent variable, X) => Simple Regression Analysis and a group of explanatory variables (independent variables, X1, X2, …). => Multiple Regression Analysis

4. 4 Case Study: Housing Prices Does AREA affect PRICE? If so, how large is the effect? What is the expected price of a house = 2000 sf?

5. 5 Initial Analysis

6. 6 Correlation  (rho): Population correlation (its value most likely is unknown.) r: Sample correlation (its value can be calculated from the sample.) Correlation is a measure of the strength of linear relationship. Correlation falls between –1 and 1. No linear relationship if correlation is close to 0.

7. 7 Correlation (  vs. r) Is 0.9584 a  or r? Sample size P-value for H 0 :  = 0 H a :  ≠ 0

8. 8 Regression Report from SG

9. 9 Fitted ModelFitted Model: Least Squares Line b1b1 b0b0 Least squares line: estimated_Price = –15.1245 + 76.1745 Area.

10. 10 Fitted ModelFitted Model: Least Squares Line