Reference no: EM131655587
Question: Refer to Problem, which referenced a list of the 100 companies perceived as having "hot growth" characteristics. The file titled Logrowth contains sales ($million), sales increase (%), return on capital, market value ($million), and recent stock price of the companies ranked from 81 to 100. In Problem, stock prices were the focus. Examine the sales of the companies.
a. Produce a regression equation that will predict the sales as a function of the other variables.
b. Determine if the overall model is significant. Use a significance level of 0.05.
c. Conduct a test of hypothesis to discover if market value should be removed from this model.
d. To see that a variable can be insignificant in one model but very significant in another, construct a regression equation in which sales is the dependent variable and market value is the independent variable. Test the hypothesis that market value is a significant predictor of sales for those companies ranked from 81 to 100. Use a significance level of 0.05 and the p-value approach.
Problem: An article in BusinessWeek presents a list of the 100 companies perceived as having "hot growth"
characteristics. A company's rank on the list is the sum of 0.5 times its rank in return on total capital and 0.25 times its sales and profit-growth ranks. The file titled Growth contains sales ($million), sales increase (%), return on capital, market value ($million), and recent stock price of the top 20 ranked companies.
a. Produce a correlation matrix for the variables contained in the file titled Growth.
b. Select the two variables that are most highly correlated with the recent stock price and produce the regression equation to predict the recent stock price as a function of the two variables you chose.
c. Determine if the overall model is significant. Use a significance level of 0.10.
d. Examine the coefficient of determination and the adjusted coefficient of determination. Does it seem that either of the independent variables' addition to R2 does not justify the reduction in degrees of freedom that results from its addition to the regression model? Support your assertions.
e. Select the variable that is most correlated with the stock price and test to see if it is a significant predictor of the stock price. Use a significance level of 0.10 and the p-value approach.
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