# Question: They are coded according to the scheme described in Section

They are coded according to the scheme described in Section 17.4. For a technology company, technology = 1 and the other dummy variables will be 0. For a financial services company, financial = 1 and the others will be 0. If a company is “other,” all six values will be 0. Thus, we need only six variables to describe the seven possible categories.

1. Generate a correlations matrix that includes variables 2–9 and 11–16. (Variable 10 would be meaningless here because its values are 1–7 for the 7 company categories.) Do the correlations “make sense” in terms of which correlations are positive and which are negative?

2. Using y = stock price (variable 8) as the dependent variable, carry out a conventional multiple regression analysis using variables 2–7, 9, and 11–16. Excel users, see note 1, which follows. Examine the partial regression coefficients to see whether their signs match the signs of the corresponding correlation coefficients associated with stock price. What percentage of the variation in stock prices is explained by the set of predictor variables?

3. Repeat step 2, but this time perform a stepwise regression analysis. Minitab and Excel users should refer to the following notes. Identify the variables that were introduced and interpret the printout. What percentage of the variation in stock prices is explained by the reduced set of predictor variables?

1. Generate a correlations matrix that includes variables 2–9 and 11–16. (Variable 10 would be meaningless here because its values are 1–7 for the 7 company categories.) Do the correlations “make sense” in terms of which correlations are positive and which are negative?

2. Using y = stock price (variable 8) as the dependent variable, carry out a conventional multiple regression analysis using variables 2–7, 9, and 11–16. Excel users, see note 1, which follows. Examine the partial regression coefficients to see whether their signs match the signs of the corresponding correlation coefficients associated with stock price. What percentage of the variation in stock prices is explained by the set of predictor variables?

3. Repeat step 2, but this time perform a stepwise regression analysis. Minitab and Excel users should refer to the following notes. Identify the variables that were introduced and interpret the printout. What percentage of the variation in stock prices is explained by the reduced set of predictor variables?

**View Solution:**## Answer to relevant Questions

The MBA program at Westmore University has undergone several dramatic changes over the past five years. During this time, the goal of the business school was to recruit as many students as possible into the MBA program in ...For the data of Exercise 18.11: a. Obtain the centered moving average for N = 4; for N = 12. b. When N = 12 months, the centered moving average is relatively smooth compared to when N = 4. Aside from the fact that it ...For the data of Exercise 18.15: a. Fit an exponentially smoothed curve with smoothing constant α = 0.6. b. For these data, describe the appearance of the exponentially smoothed curve when the smoothing constant is α = 0.0; ...An appliance repair shop owner has fitted the quadratic trend equation ŷ = 90 + 0.9x + 3x2 to a time series of annual repair orders, with y = the number of repair orders and x = 1 for 2005. Forecast the number of repair ...The following data are the wellhead prices for domestically produced natural gas, in dollars per thousand cubic feet, from 2001 through 2008. Given these data and the trend equations shown here, use the MAD criterion to ...Post your question