The research questions I wish to answer using multiple regression are:

Which variables can be used to predict tourAwesomeness?

Determine how much variance in tourAwesomeness can be accounted for by all the significant variables?

Determine how much variance is tourAwesomeness can be accounted for by each significant variable after accounting for the other variables.

I ran a bivariate correlation between all variables. I checked to see which variables were significant and had a correlation above .3, (Pallant, 2010, p. 158). I found two variables: RideDays (-.425) and Blog (.304). I drew a Venn diagram to picture the analysis. I checked the sample size with two independent variables: the sample size is more than 50 + 8*2 = 50 + 16 = 66. I ran a standard multiple regression with dependent variable tourAwesomeness and independent variables Blog and RideDays, to determine a + b + c. I checked the collinearity statistics to ensure that tolerance > .10 and VIF < 10, see Table 8. I examined the Normal P-P plot of regression standardized residuals which showed a near linear line. I examined the scatterplot and did not see any clear or systematic pattern to the residuals. These test indicate that the model assumptions were met. I examined the model summary and noted that 25% of the variance in tourAwesomeness can be accounted for by RideDays and Blog, see Table 9. In the Venn diagram a + b + c = 25%. I ran a hierarchical regression with Blog in step 1 and RideDays in step 2. That is, I wanted to see how much variance in tourAwesomeness was accounted for by RideDays after controlling for Blog, or a in the Venn diagram. I examined the model summary for R^{2} change, see Table 9, and determined that 15.8% of tourAwesomeness is accounted for by RideDays after controlling for Blog, so a = 15.8%. I ran a hierarchical regression with RideDays in step 1 and Blog in step 2. That is, I wanted to see how much variance in tourAwesomeness was accounted for by Blog after controlling for RideDays, or c in the Venn diagram. I examined the model summary for R^{2} change, see Table 9, and determined that 7% of tourAwesomeness is accounted for by Blog after controlling for RideDays, so c = 7%. Finally, I calculated the value of b using the values of a + b + c = 25%, a = 15.8%, c = 7%; therefore, b = 2.2%.