# Question: In the following regression X monthly maintenance spending dollars

In the following regression, X = monthly maintenance spending (dollars), Y = monthly machine downtime (hours), and n = 15 copy machines.

(a) Write the fitted regression equation.

(b) State the degrees of freedom for a two-tailed test for zero slope, and use Appendix D to find the critical value at α = .05.

(c) What is your conclusion about the slope?

(d) Interpret the 95 percent confidence limits for the slope.

(e) Verify that F = t2 for the slope.

(f) In your own words, describe the t of this regression.

(a) Write the fitted regression equation.

(b) State the degrees of freedom for a two-tailed test for zero slope, and use Appendix D to find the critical value at α = .05.

(c) What is your conclusion about the slope?

(d) Interpret the 95 percent confidence limits for the slope.

(e) Verify that F = t2 for the slope.

(f) In your own words, describe the t of this regression.

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

In the following regression, X = total assets ($ billions), Y = total revenue ($ billions), and n = 64 large banks. (a) Write the fitted regression equation. (b) State the degrees of freedom for a two-tailed test for zero ...Choose one of these three data sets. (a) Make a scatter plot. (b) Let Excel estimate the regression line, with fitted equation and R2. (c) Describe the t of the regression. (d) Write the fitted regression equation and ...Below are fitted regressions based on used vehicle ads. Observed ranges of X are shown. The assumed regression model is Asking Price = f (VehicleAge). (a) Interpret the slopes. (b) Are the intercepts meaningful? Explain. (c) ...A regression model to predict Y, the state burglary rate per 100,000 people for 2005, used the following four state predictors: X1 = median age in 2005, X2 = number of 2005 bankruptcies, X3 = 2004 federal expenditures per ...The same data set from exercise 13.19 also has gender information for each engineer. The binary variable Male = 1 indicates the engineer is male and Male = 0 indicates the engineer is female. Run the regression with Salary ...Post your question