Example from book: Multiple Correlation and regression--interaction term


Are Auction Prices of Clocks related to Number of Bidders and age of clocks?

Is there an interaction between these two factors?

  • There is a Comma-delimited ASCII files of the  data as CXA11_01.prn which you can download to your disk by shift-click or right click. Bring it into EXCEL and immediately do a SaveAs to your A: disk, specifying file type EXCEL before you start on the project.  It's not enough to add the .xls  extension on the file.
  • Clock Auctions:

    1. generate a scatter plot of price vs. age of clock with trendline, equation and r-squared. don't force intercepts to zero. comment on the appearance of the plot and the significance of r-squared.
    2. do the same for price vs. number of bids
    3. produce a correlation matrix and comment on what it means
    4. produce a multiple regression analysis with alpha =5% for the confidence intervals on the coefficients. from this table, what is the equation of the line? referring to Pvalues a t statistics, are the intercept and regression relationship statistically significant at the 5% level?  What does the P value mean and how does it relate to alpha?
    5. put in another column, multiplying number of bids times age and use this as a third independent variable.  What is the practical significance of this variable?
    6. repeat the regression anlysis including the NB*Age (interaction) variable.  referring to the t statistics and P values, as well as the reduction in error mean square by including this variable, does it look like a useful thing to do?  Test this by doing an Ftest on difference in error mean Square for the full model vs. the reduced model (leaving out the interaction) dividing this reduction by residual mean square of the full model.
    7. What is the equation for the full model? What practical significance might this have? Following from your analysis how might you speculate about a possible "way things work" in clock auctions?