This data table contains accounting and financial data that describe 324 companies operating in the information sector
Question:
(a) Thinking marginally for a moment, would you expect to find a correlation between the log of the total assets and the log of the cost of goods sold?
(b) Does the correlation between the explanatory variables change if you work with the data on the original scale rather than on a log scale? In which case is the correlation between the ex-planatory variables larger?
(c) In which case does correlation provide a more useful summary of the association between the two explanatory variables?
(d) What is the impact of the collinearity on the standard errors in the multiple regression using the variables on a log scale?
(e) We can see the effects of collinearity by constructing a plot that shows the slope of the multiple regression. To do this, we have to remove the effect of one of the explanatory variables from the other variables. Here’s how to make a so-called partial regression leverage plot for these data. First, regress Log R&D Expenses on Log Cost Goods Sold and save the residuals. Second, regress Log Assets on Log Cost Goods Sold and save these residuals. Now, make a scatterplot of the residuals from the regression of Log R&D Expenses on Log Cost Goods Sold on the residuals from the regression of Log Assets on Log Cost Goods Sold. Fit the simple regression for this scatterplot, and compare the slope of this simple regression to the partial slope for Log Assets in the multiple regression. Are they different?
(f) Compare the scatterplot of Log R&D Expenses on Log Assets to the partial regression plot constructed in part (e). What has changed?
Fantastic news! We've Found the answer you've been seeking!
Step by Step Answer:
Related Book For
Statistics For Business Decision Making And Analysis
ISBN: 9780321890269
2nd Edition
Authors: Robert Stine, Dean Foster
Question Posted: