{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 explanatory variables larger? because the correlation between the explanatory variables on the original scale is D and the correlation on the log scale is D. Thus. the {Round to two decimal places as neededJ {5) In which case does correlation provide a more useful summary of the association between the two explanatory variables? Correlation provides a more useful summary of the association hen-teen the two explanatory variables on the E scale because V (d) What is the impact of the collinearity on the standard errors in the multiple regression using the variables on a log scale? Since the variance inflation factor is , the standard errors of the estimated slopes are by a factor of than if the explanatory variables were uncorrelated. (Round to two decimal places as needed.)(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? The partial slope for Log Assets in the multiple regression is and the slope from the simple regression of the residuals is Thus, the slopes are (Round to two decimal places as needed.)= Homework: HW CH24 Question 7, 24.1.37-T HW Score: 26.68%, 3.2 of 12 points Part 1 of 6 Points: 0.36 of 1 Save The accompanying data table contains accounting and financial data that describe 396 companies operating in the semiconductor industry. The variables include the expenses on research and development (R&D), total assets of the company, and the cost of goods sold. Use the natural logs of all variables and fit the regression of Log R&D Expenses on Log Assets and Log Cost Goods Sold. Complete parts (a) through (f) below. Click the icon to view the table of data. (a) Thinking marginally for a moment, would you expect to find a correlation between the log of the total assets and the log of cost of goods sold? O A. No, large corporations tend to have large values for assets, but their costs are not much different from smaller corporations. O B. No, large corporations tend to have large values for costs, but their assets are not much different from smaller corporations. O C. No, while there may be correlation between total assets and costs, the logs of total assets and costs suppresses that correlation. O D. Yes, large corporations tend to have large values for both assets and costs