Analytics Magazine Analytics Magazine, November/December 2014 - Page 71

Figure 1: Daily bicycle transits by date. This graph shows a nice trend of more cycling in the summer months and less cycling in the winter. There are two outliers: June 1 and Sept. 8. data was ready for analysis. The 2012 year data was “cleaner” than the 2013 data, so that is what is used here. Unlike many data sets, the historic weather information is also included. While this doesn’t sound like a big deal, it makes analysis much easier. It is natural to ask if the weather, as measured by daily average outside air temperature, has an effect on cyclists. We can also use this data to think about trail utilization during the week as opposed to the weekend. This is interesting because in major cities, bicycle trails are not just for recreation but are also used by a large number of commuters for work. Here, the “WEEKDAY()” function in Excel was handy to identify the weekdays vs. weekends. We have chosen to compare the behavior of cyclists Figure 2: Daily bicycle transits as a function of temperature. Each rise in daily average temperature of 1 degree Fahrenheit translates to approximately 10 additional riders (Regression p-value = 0). a na l y t i c s n o v e m b e r / d e c e m b e r 2 014 | 71