READ THESE INSTRUCTIONS In this exam we will use another bikeshare dataset, this

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READ THESE INSTRUCTIONS
In this exam we will use another bikeshare dataset, this

READ THESE INSTRUCTIONS
In this exam we will use another bikeshare dataset, this time from Washington, D. C. You do not need to do any analysis yourself, but if you wish to, the relevant file is DC bikeshare by day.sav. You will, however, need to open the output file, DC bikeshare day analysis.spv, in SPSS. Go to File, Open, Output. I have emailed both of these files to you.
The heart of this data set is two years (1/1/11 to 12/31/12) of bike rental data from Capitol Bikeshare, in Washington, D.C. I have converted normalized temperature, humidity, and wind speed to actual values, and I have converted Celsius temperatures to Fahrenheit, and kph wind speeds to mph. I have added a variable (MSeason) that follows meteorological conventions regarding the four seasons.
The list of variables is in the file bikeshare_varlist.pdf (see email). You may want to refer to it to make sense of some of the output. I put it in a separate file, rather than in the quiz, so you can keep it open in a separate window or print it.
These data were collected in order to determine how, and how well, climate/weather variables and calendar variables predict the number of bikes rented on a given day.
The questions in this exam are intended as, among other things, a reminder that data analysis is not about performing this or that procedure but rather about trying to understand the conditions or events described, however imperfectly, by the data.
There are 30 questions, worth 66 points.

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