Testing for Multiple Regression
For this assignment, I used the High School Long Study Dataset. The question I constructed is; how does the students’ sex relate to the number of hours they spend hanging out with friends on a typical school day and their parents’ highest level of education? The hypothesis is that there is no relationship between the students’ sex, and their parents
highest education and how many hours they spend hanging out with friends on a typical school day. The significance of the ANOVA is .047 which is less than 0.5, meaning can accept the hypothesis. There is a correlation between the variables of gender, parents education and hours spent with friends. Additionally, the adjusted R square is 0.001, which again means we can accept the hypothesis that there is a correlation between variables. According to the coefficient chart below, the significance of the hours spent hanging out with friends and the respondents gender is .018 whereas the significance of the respondents gender and parents highest degree earned is .620. We can speculate that there is higher correlation between the parents degree and the respondents gender than there is between respondents gender and hours spent hanging out with friends.
One implication for social change is that parents who have higher earned degrees allow their children to spend more time hanging out with their friends than those who have lower earned degress.