I’d like to discover which “calendar factors” (e.g. day of the week, month) have the strongest relationship with whether or not a particular product is sold at least once. For days when the product was sold, I have data like this:
Date Day of Week Day Type Month 01-01-2014 Wednesday Weekday January 01-13-2014 Monday Weekday January 02-09-2014 Sunday Weekend February 02-15-2014 Saturday Weekend February 02-16-2014 Sunday Weekend February 02-23-2014 Sunday Weekend February
If we pretend that this is the entire dataset, we see that the product was sold mostly on Sundays in February.
I’ve come up with a simple way to rank each individual calendar factor (e.g. month) as well as a few combinations (e.g. day type + month) by creating a ratio of “sale days” vs. the entire population: using the example data, Wednesday + January would have a rank of 1 / 5. However, I’m struggling to determine which factors and/or combination of factors are most significant without simply picking the highest-ranking one.
I feel like there must be a stronger mathematical approach to solving this kind of problem. Any ideas? Also, how would you classify this problem?