The results of the Chi-Square test suggested that I should reject my null hypothesis that the proportion of people in their 30s who use CitiBike for commuting is independent of the proportion of people in their 20s who use CitiBike for commuting at a significance level of α = 0.05.
The strengths of this analysis were that the chi-square test is robust with respect to the distribution of the data. It does not require that variances are equal among the two samples being tested. Also, the detail required to conduct the Chi-Square test provides a more detailed understanding of the Chi-Square statistic and the way it is calculated. 
The weaknesses of this analysis are that ultimately, I was only able to determine that the proportion of people in their 30s who use CitiBike for commuting is not independent of the proportion of people in their 20s who use CitiBike for commuting. I was not able to address my initial hypothesis which was that the proportion of people in their 20s who use CitiBike for commuting is larger than the proportion of people in their 30s who use CitiBike for commuting.