Methodology
To test my hypothesis, I used the Chi-Square Test for Proportions. I chose this statistical test because I am comparing two proportions - proportion of 30s weekend riders and proportion of 20s weekend riders. My data is categorical. Either a rider is in their 20s or their 30s. Either a ride occurs on a weekend or a weekday. The Chi-Square test is also the test that was recommended by my peer reviewer, Nathan Caplan.
INSERT CONTINGENCY TABLE HERE
Figure 3: Chi Square contingency table for my two categories (20s riders and 30s riders). I used the contingency table to calculate the expected ratio for each cell.
My calculated Chi-Square value was 16.6. I compared this value to the Chi-Square table for 1 degree of freedom and significance level = 0.05. The value obtained from the Chi-Square table for 1 degree of freedom and significance level = 0.05 was 3.84. Since my Chi-Square value 16.6 > 3.84, I rejected the null hypothesis that the proportion of weekend rides is independent of age.
An alternative test that I could have used but did not