Study Guide for the Final Exam

 

For the final exam, you may bring 2 pages of formula sheets.  The exam is closed-book and closed-notes.

 

Review these pages in the text:

1.  Regression Analysis (P. 36-94)

2.  The Analysis of Variance (P. 101-105)

 

Also review the corresponding Powerpoint slides.

 

Practice Problems:

 

1.  A sample of 25 computer hardware companies (file: computer.sf3) taken from the Stock Investor Pro provided the following data on the price per share, book value per share, and the return on equity per share for each (Stock Investor Pro, American Association of Individual Investors, August 21, 1997).

a.  Develop an estimated regression equation that can be used to predict the price per share given the book value per share.  At the 0.05 level of significance, test for a significant relationship.

b.  Did the estimated regression equation developed in part (a) provide a good fit to the data? Explain.

c.  Develop an estimated regression equation that can be used to predict the price per share given the book value per share and the return on equity per share.  At the 0.05 level of significance, test for overall significance.

 

2.  State the assumptions of the error term in multiple regression.

 

3.  We use ANOVA to compare means from different population groups.  Why do we call it Analysis of Variance?  Why not Analysis of means?

 

4.  Consider a regression study involving a dependent variable y, a quantitative independent variable x1, and a qualitative variable with two levels (level 1 and level 2).

a.  Write a multiple regression equation relating x1 and the qualitative variable to y.

b.  What is the expected value of y corresponding to level 1 of the qualitative variable?

c.  What is the expected value of y corresponding to level 2 of the qualitative variable?

d.  Interpret the parameters in your regression equation.

 

5.  What are the differences between regression and ANOVA?

 

6.  Explain both regression and ANOVA in terms of common variation and specific variation.

 

7.  A sample multiple choice question:

 

In regression analysis, an outlier is an observation whose

            a.   mean is larger than the standard deviation

            b.   residual is zero

            c.   mean is zero

            d.   residual is much larger than the rest of the residual values