One day I had a Shower Thought™. If you were to try to buy a 2000" TV today, how much would it cost and how much would it weight.
So I decided I'd try my hand and figuring this out based on data I could glean from current TV sizes and prices. To do this I took used the Best Buy API to pull down all of the televisions they have in their database and then get the price, weight and size1. Then taking that data I transformed it into two data sets, price vs size and weight vs size. Then taking that data I inserted it into Highcharts using a regression library2 to get a best fit line. I tried a couple of different line models until I found what I think is the best fit3.
To get the data from the Best Buy API I made two queries (five if you count the ones used to get the pagination results)
After pushing the data into Highcharts and running the regression library2 I got the following formulas
y = 1.59x2 + -85.52x + 1407.76
y = 0.03x2 + -0.91x + 15.26
1 Since I did this in an automated fashion some of the entries were not formatted consistantly and so I threw them out. For example some of the sizes were denoted as
54-1/2 instead of
54.5 and rather than code up all the possibilities, I just removed them