Submitted by: Yanmei Guan @yg833, Samantha Jeanne Falk @sjf374, Qinyu Goh @qg412
ABSTRACT: 
For this Citibike mini project, our team wanted to test if riders were more keen on riding Citibike on Saturdays than Sundays. The idea was based on the rationale that there are more places of interests closed on Sundays than Saturdays. To test our idea, we looked at Citibike data from 2016 and selected 1 month of data from each season -February for Winter, May for Spring,  August for Summer, and November for Fall. Seasonality is important considering that bike riding is outdoors; cooler temperatures during some seasons will affect ridership. Ergo by sampling 4 months across the year, we are hoping to see a more fuller picture. 
We initially visualized the counts of rides by weekday using scatter plot, mean with error bars, and box plot with median of riders, and it looked like there maybe some differences. Especially considering that the mean number of rides for Saturday was 32884.13 with a standard deviation 12260.51 and the mean number of rides for Sunday was 28834.11 with a standard deviation of 11372.29. Then, we ran a two sample t-test on the counts from Saturdays and Sundays across the 2016 year, and it returned a t-statistic of 0.985 and a p-value of 0.332. As the p-value is greater than 0.05, we fail to reject the null hypothesis and therefore conclude that there the mean bike trips on Saturdays are the same or less than the mean of bike trips on Sundays in the 4 months of 2016, at a significance level of 0.05. 
INTRODUCTION: 
Citibike is New York City's (NYC) very own bicycle sharing program. Functioning as a docked bicycle sharing system, users either purchase day passes or annual membership in order to unlock a bicycle at a specific station and ride it to another station to return the bicycle.  Since its inception in 2013, Citibike has quickly grown to become a staple mode of transportation in NYC, even beating taxi in travelling time in certain instances \citep{bliss2017} .  
Given the popularity of Citibike in NYC,  the team set out the explore Citibike's readily available public trip data to see if interesting trends of usage, as well as the behavior of users, can be distilled. 

Idea/Question