You have collected data from a sample of 25 middle school students on two variables:

1) Commitment to school: Those who score high on this measure have high levels of commitment to school. It is a continuous variable formed by the addition of multiple questions asking the students about the amount of efforts they put into school work.

2) Perception of the police: Those who score high on this measure have high levels of positive perceptions of the police. It is also a continuous variable formed by the addition of multiple questions asking the students about their opinion on various aspects of police work.

Your research question is: Does middle-school students' commitment to school affect their perceptions of the police?

Here are your data:

Commitment to school	Perception of the police
16	17
17	20
19	21
25	23
15	17
16	16
8	16
27	26
21	22
26	20
28	25
24	23
17	16
15	10
13	15
20	20
22	21
24	23
20	17
22	20
21	24
16	19
25	22
12	20
17	19

1. Graph the two variables with the correct independent variable on the x axis and dependent variable on y axis. Does it look like there's a relationship? Does it look at least approximately linear?

1. Below is the SPSS output of the correlation coefficient between the two variable - interpret this coefficient.

Correlations
	perception of police	commitment to school
perception of police	Pearson Correlation	1	.748**
Sig. (2-tailed)		.000
N	25	25
commitment to school	Pearson Correlation	.748**	1
Sig. (2-tailed)	.000
N	25	25
**. Correlation is significant at the 0.01 level (2-tailed).

1. Calculate and interpret the value of R²based on the information from step b.

1. Below is the SPSS output of the regression coefficients - interpret them.

Coefficientsa
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	-1.187	3.883		-.306	.763
commitment to school	1.048	.194	.748	5.398	.000
a. Dependent Variable: perception of police

1. What is the predicted score of perception of the police for a student who has a school commitment score of 10, 15 and 20? (hint: write out the regression equation first)