I am working on a project for a Masters Project. The town I am looking at Switched to a Fareless system in Feb 1, 2011. I want to look and see if this increased ridership by a substantial amount. I have the following
for data and have it drilled down further to even amount of riders per day per hour since 2008. But I don't think that detail of information is needed I am thinking looking by weeks.
The thing is the town and student base of the town is growing at super fast rates. In 2011 there were 400 new students added to campus but there were 1,200 continuing students, so a net gain of 1,600 students. The town is only 54,000 people with the college only being about 26,000 (as of Fall 2012).
The way I was going to see if the new Fareless system was working as planned or not was to use time-series forecasting and use just the "pre-fareless" data and forecast out what the numbers would be expected to be. Compare those to the "post-fareless" data and see if it falls into the confidence intervals of the "pre-fareless" data. If it is outside of it then the change in fare was a success? The student growth has been pretty constant since 2008 if not stronger in 2009/2010 then lowering 2011 and 2012.
I have R/SPSS/STATA/Excel access. I am pretty competent with SPSS and very new at R and STATA. All help/advice would be great. Thank you in advance.
So far it seems that ARIMA is the method to use to analyze this data. Would still love to hear other peoples thoughts and ideas on maybe other items that I might be missing other than population growth.