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BA 275 Quantitative Business Methods

BA 275 Quantitative Business Methods. Agenda. Simple Linear Regression Introduction Case Study: Housing Prices Final Examination 7:30A.M., Thursday, 12/ 7/2006 Owen 102 Check the seating chart when you arrive. Open book/notes. Need a calculator.

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BA 275 Quantitative Business Methods

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  1. BA 275 Quantitative Business Methods Agenda • Simple Linear Regression • Introduction • Case Study: Housing Prices • Final Examination • 7:30A.M., Thursday, 12/ 7/2006 • Owen 102 • Check the seating chart when you arrive. • Open book/notes. Need a calculator. • Comprehensive: Chi-Squared Test + Regression Analysis: 60 – 70%. • Turn in SG#3 and CD#3 at the beginning of the examination.

  2. 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

  3. 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?

  4. Initial Analysis

  5. Fitted Model b0 Sb1 Sb0 b1 H0: b1 = 0 Ha: b1≠ 0 Degrees of freedom = n – 2

  6. Fitted Model b0 Sb1 Sb0 b1 Degrees of freedom = n – 2

  7. Correlation • r (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.

  8. Correlation (r vs. r) Sample size P-value for H0: r = 0 Ha: r≠ 0 Is 0.9584 a r or r?

  9. A Good Fit? SS = Sum of Squares = ???

  10. Prediction and Confidence Intervals • What is your estimated price of that 2000-sf house on the 9th street? • Quick answer: estimated price = -15.1245 + 76.1745 (2) = 137.2245 • What is the average price of a house that occupies 2000 sf? • Quick answer: estimated price = -15.1245 + 76.1745 (2) = 137.2245 • What is the difference?

  11. Prediction and Confidence Intervals

  12. Prediction and Confidence Intervals Prediction interval Confidence interval

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