An interesting article was brought to my attention in a comment from a week ago. I finally had the chance to analyze the data myself.

The thing that struck me is that the top two states with job growth didn’t have changes to the minimum wage (California and Nevada), while the state with the highest job loss (New Jersey) did have changes to the minimum wage. Something really wasn’t adding up.

Not just that but there are the big states that didn’t change the minimum wage went up fastest. California went up hugely — and it itself is huge. Comparing a behemoth like California to something like Washington DC or Rhode Island is stupid and best and outright contortion of data into lies at worse.

Similar stupid things can be done on the other side of the argument. Look, 31 states that didn’t raise minimum wage by saying things like the state with the highest job loss also messed with the wages. Data taken out of context is lies.

So, basically I used Mathematica to analyze the data by enriching it with population data from the US Census and computing a weighted-mean of the data and came up with an interesting result — the opposite of what the original article reported.

With a population-weighted calculation, states that did not increase the minimum wage at a 1.02% increase in employment compared to 1.00% increase in states that did increase the minimum wage. Yes, it’s close, but it still is the reverse of the original article.

I call bullshit.

Here’s my analysis of employment data as a PDF, HTML, or a fully editable CDF for you play with as well if you have Mathematica at your disposal. All of the work is shown for your convenience.

The moral of the story is that one needs to be aware of what spin is being put on data before you can really believe the analysis that you’re reading.

TL;DR: There are lies, damn lies, and statistics – be careful what you believe.