1. Given the following data, what would be the conclusion?

1. Given the following data, what would be the conclusion?

Coefficientsa

Model Unstandardized Coefficients Standardized Coefficients t Sig.

B Std. Error Beta 

1 (Constant) -5644.144 919.913 -6.136 .000

percentpoverty 18.981 6.438 .166 2.948 .003

percentmale 118.623 19.425 .345 6.107 .000

a. Dependent Variable: rate of ubev

a. Neither percent in poverty nor percent male is significantly related to the rate of unlawful breaking and entering of vehicles.

b. Percent in poverty and percent male are significantly related to the rate of unlawful breaking and entering of vehicles.

c. Only percent in poverty is significantly related to the rate of unlawful breaking and entering of vehicles

d. Only percent male is significantly related to the rate of unlawful breaking and entering of vehicles.

2. Since researchers cannot always conduct true experiments, one must control for spurious relationships.

a. True

b. False

3. A partial cross tabulation table examines the relationship between three variables to control for spurious relationships.

a. True

b. False

4. To use the multiple regression equation the dependent variables and all of the independent variables have to be measured at the interval or ratio level.

a. True

b. False

5. In order to compare the effects of two or more independent variables on a dependent variable the beta weight would be the proper statistic to use.

a. True

b. False

6. We are interested in understanding the causes of post-traumatic stress disorder (PTSD) among police officers. We draw a sample of 100 officers from an urban police department and collect three pieces of information:

a) Whether they have or are currently experiencing the symptoms of PTSD

b) The number of years they have been on the police force

c) Whether or not they used their firearm to shoot someone during their duties

We estimate a linear probability model with PTSD as our dependent variable and the number of years on the force as our only independent variable. We get the following results:

Coefficientsa

Model Unstandardized Coefficients Standardized Coefficients t Sig.

B Std. Error Beta 

(Constant) .702 .064 10.969 .000

Number of Years on Force -.043 .006 -.609 -7.167 .000

R2 = .37

With these results, answer the following questions:

a. Write out the full regression equation.

b. Interpret the constant.

c. Interpret the slope coefficient.

d. Using an alpha of .05, what is your decision about the null hypothesis: byrsontheforce = 0? Explain.

e. Interpret the value of R2.

f. What is the predicted probability of having PTSD for an officer who has 5 years on the force?

g. What is the predicted probability of having PTSD for an officer who has 15 years on the force?