Our group used two types of testing methods which are correlations/regressions and the ANOVA table, to test our hypothesis for the statistical analysis. Both tests showed that we fail to reject our null hypothesis. This means that there is no difference between the amount of time spent commuting to school and the average time studying per week.
We used correlation/regression testing to create scatter plots that represents the relationship between two quantitative variables. The correlation coefficient (r) measures the strength of a linear line between two variables. Referring to the scatter plot, our R squared value or correlation coefficient of 0.0026 indicates no correlation because 0.0026 is close to the value of zero. In other words, there is no correlation between time spent commuting per week and the average time spent studying per week.
The linear regression table indicates that since the correlation coefficient was found to be smaller than the p level for the independent variable of time spent commuting per week (measured in hours), we fail to reject the null hypothesis.
By using a significance Level of 0.05, p-value of 0.599 is greater than 0.05. We do not have enough evidence to reject the hypothesis that the slope is equal to zero. Again, there is no association between the two variables. Time spent studying per week is not associated with the Average time spent studying per week
Utilizing the ANOVA table with categories of 15-minute increments related to commute time, we also fail to reject the null hypothesis due to the F-statistic being smaller than the F-critical value. The ANOVA table illustrates that our F-statistic of 1.63728 is less than F-critical value of 1.8511. Therefore, the time spent studying for those who live on campus may be equal to the amount of time spent studying for those who live further away from campus.
Overall, our results were not connected to our findings in the literature. Despite the fact that some studies state that there is a correlation between commute and study time, there is still not enough evidence that students who live further away from campus spend less time studying compared to students who live on campus.