The data set contains three variables:

1. Drug use (the number of times an individual has used drugs in the last month excluding alcohol).
2. Gender (coded as - 0 = male, 1=female)
3. Employment Status (coded as - employed full time = 1, employed part time = 2 , unemployed =3)

Data Set

Research Subject	Drug Use	Gender	Employment Status
1	1	1	1
2	1	1	2
3	2	0	3
4	4	0	1
5	2	1	2
6	9	0	3
7	7	1	2
8	5	1	3
9	0	0	1
10	3	0	1
11	5	0	2
12	2	1	3
13	3	1	3
14	4	1	2
15	5	0	1
16	8	1	2
17	1	1	3
18	5	0	1
19	3	0	2
20	5	0	3

1. Imagine that you hypothesize that there is a relationship between gender and drug use. You decide to run a regression on the data. Please do the following.
   1. Run a bivariate regression on these two variables in SPSS (gender, drug use). Report the following:
      1. Assume that you met all of the assumptions to run a bivariate regression (even if you did not). Report the results for the bivariate regression you ran as you would report them in a journal article. Make sure you include all relevant information. You should report the results for the following:
         1. The F test
         2. R²
         3. B (slope) with significance (Remember this part of the interpretation is different becuase it is a dummy variabe).
2. Imagine that you hypothesize that there is a relationship between employment status and drug use. You decide to run a regression on the data. Please do the following.
   1. Assume you meet all required assumptions for the test. (Normally you would test them, but technically this will be a multiple regression so do not worry about the assumptions for now).
   2. Run a linear regression in SPSS with Drug Use as your outcome variable, and employment status as the predictor variable. (To do this you will need to recode employment status into multiple dummy variables). Review the video if you are confused.
      1. Report the B (slope) of your results. (Once again remember the interpretation is different).