Research Project(7): Examine Correlation between Quantitative Variables with SAS

Introduction

This post is for the week 3 assignment of the Coursera course Data Analysis Tools by Wesleyan University. It’s the 2nd course for the Data Analysis and Interpretation specialization.

This time I used Addhealth dataset. I examined the relationship between hours watching TV per week and hours playing video or computer games per week. I am also interested in predicting the variability in hours playing games by hours watching TV.

CODE

CODE

Output

Scatterplot

OUTPUT1

Correlation

OUTPUT2

Interpretation

From the scatter plot, we can see that there is a weak linear relationship between two quantitative variables H1DA8 and H1DA10.

The pearson correlation coeficients also indicated that the linear relationship between these two variables is weak, r=0.28822. Also, the correlation is statistically significant, p < .0001.

RSquared=0.28822^2=0.083

8.3% of the variability in hours playing video or computer games per week can be predicted by hours watching TV per week.

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