Cheating Age or Aging Cheaters

This article is a bit over a year old but I ran across it today and was struck by the the easy acceptance of the conclusions.

Since it's behind a pay wall, here's a short summary: A study was done using data from the Ashley-Madison dating web site. For those who missed last year's headlines, this site is for people already in a committed relationship who want to find someone to cheat with. Researchers looked at the ages of registered users and found a statistically significant bump in the distribution for ages ending in "9".

The conclusion is that people are more likely to cheat when they are approaching a milestone birthday (30, 40, 50, etc.). They get stressed about aging and reach out for a little excitement.

That's certainly a possible explanation. However,  I think they overlook another simpler explanation - people lie about their age. If you're anywhere in the 40 to 45 range and you want to claim you're in your 30's then 39 is more believable than 38, 37, 36, etc. 

I think this explanation is at least as likely as the first. Keep in mind, everyone on this web site is trying to CHEAT. They're all dishonest. Why wouldn't they lie about their age? 

Data matters - but only if you accept it.

In my classes I regularly tell students that statistical controversy is rarely about the number crunching, it's about the data.

I recently posted a link to an article about political polling. Summary? The data was wrong so the predictions were wrong.

However, there's another data problem and, perhaps, it's the most common problem. What should you do when you think something is true but you have data that contradicts it? Statistically, you're supposed to go with the data and change what you thought was true.

People who know statistics might recognize this situation. You have a null hypothesis, Ho, and the data leads to a small p-value. This means you should reject Ho and conclude that the alternative hypothesis, Ha, is true instead.

Unfortunately people tend to fall the other way. If the data contradicts their beliefs, they reject the data. This is true even among those who have scientific and statistical training.

The People's Pharmacy recently wrote about a new study that "exonerates" eggs. This is one of many studies that contradict that old idea the eggs are unhealthy because of dietary cholesterol. All the data shows that eggs are healthy. Yet the article states:

"It’s hard to teach old dogs new tricks. Many health professionals will find it challenging to accept the new data from the Finnish Heart Study. But the writing has been on the wall for quite a few years that the evidence supporting dietary cholesterol as the culprit behind heart disease was weak."

Health professionals, people with significant scientific training, will stick with their old beliefs and reject the data.

The limits and challenges of public opinion polling

With the Presidential primaries in full swing, the polls were pretty far off in Michigan.

This article provides some possible explanation. It also talks about the difficulty of getting proper samples and the importance of asking the right questions.