Bivariate data was collected from a random sample of colleg…

 Bivariate data was collected from a random sample of college students, where the independent variable x is the number of hours per week the student spent working at a part-time job and the dependent variable y is the student’s overall satisfaction with their college experience (measured on a 100-point scale). SPSS was used to create a scatter plot of the data and to construct a simple linear regression model. A portion of the SPSS output appears below.         Use the SPSS output to fill in the blanks: From the SPSS output, the value of Pearson’s correlation is [r1]. Based on this and the scatter plot, there appears to be [r2]. The P-value for the ANOVA test is P=.0004. Testing at the .05 level of significance, the sample evidence is [a1] to conclude that a linear correlation exists between x and y. The proportion of the variance in a student’s overall satisfaction with college that can be explained by the time the student spends working at a part-time job is [a2]. Using the linear regression model, a student who spends 9 hours per week working at a part-time job is expected to have an overall satisfaction score of approximately [score]. Based on the linear regression model, an increase of one hour in the time a student spends working at a part-time job decreases the student’s expected overall satisfaction score by [m] points.