# Question

A regression model to predict Y, the state-by-state 2005 burglary crime rate per 100,000 people, used the following four state predictors: X1 = median age in 2005, X2 = number of 2005 bankruptcies per 1,000 people, X3 = 2004 federal expenditures per capita, and X4 = 2005 high school graduation percentage.

(a) Write the fitted regression equation.

(b) Interpret each coefficient.

(c) Would the intercept seem to have meaning in this regression?

(d) Make a prediction for Burglary when X1 = 35 years, X2 = 7.0 bankruptcies per 1,000, X3 = $6,000, and X4 = Burglary 80 percent.

(a) Write the fitted regression equation.

(b) Interpret each coefficient.

(c) Would the intercept seem to have meaning in this regression?

(d) Make a prediction for Burglary when X1 = 35 years, X2 = 7.0 bankruptcies per 1,000, X3 = $6,000, and X4 = Burglary 80 percent.

## Answer to relevant Questions

If you did not already do so, request a plot of residuals versus the fitted Y. Is heteroscedasticity a concern? A researcher used stepwise regression to create regression models to predict BirthRate (births per 1,000) using five predictors: LifeExp (life expectancy in years), InfMort (infant mortality rate), Density (population ...Refer to the ANOVA table below. (a) State the degrees of freedom for the F test for overall significance. (b) Use Appendix F to look up the critical value of F for α = .05. (c) Calculate 2 the F statistic. Is the ...(a) Plot the voter participation rate. (b) Describe the trend (if any) and discuss possible causes. (c) Fit both a linear and a quadratic trend to the data. (d) Which model is preferred? Why? (e) Make a forecast for ...(a) Plot the data on law enforcement officers killed. (b) Describe the trend (if any) and discuss possible causes or anomalies in the data. (c) Would a fitted trend be helpful? Explain. (c) Make a forecast for 2009 using ...Post your question

0