I think the experimental evidence for religion making people happier is horribly flawed (i might be a bit biased given i worked in a lab who was doing work on the subject). Here are some reasons:

Generally the researchers in the field assume that you can just do a linear analysis of religiosity and happiness, meaning using a scale of not religious to very religious and then making not religious=atheist, which is clearly not a good assumption. In fact studies have shown in the past a curvilinear relationship where the "more certain" positions of atheist and theist are as happy as each other . Also, even making sure that the people in the atheist pool are atheists is hard. If i remember correctly the pew research that showed a certain number of atheists in the country also found 40% of those atheists believed in god.

Second reason is : generally the studies use church attendance as its operational definition of religion which does not control for the social support that being in a church provides and when studies control for that generally they find no difference.

Now if this post is about if its true that it makes people happier what does that mean then please ignore.

Edit: i hope thats better

religion making people __ is horribly flawed


do a linear analysis of __ which is clearly not


Now if this post is about if its true that it makes people happier what does that mean then please ignore.

You lost me. More punctuation, maybe?

Religion, happiness, and Bayes

by fortyeridania 1 min read4th Oct 201127 comments


Religion apparently makes people happier. Is that evidence for the truth of religion, or against it?

(Of course, it matters which religion we're talking about, but let's just stick with theism generally.)

My initial inclination was to interpret this as evidence against theism, in the sense that it weakens the evidence for theism. Here's why:

  1. As all Bayesians know, a piece of information F is evidence for an hypothesis H to the degree that F depends on H. If F can happen just as easily without H as with it, then F is not evidence for H. The more likely we are to find F in a world without H, the weaker F is as evidence for H.
  2. Here, F is "Theism makes people happier." H is "Theism is true."
  3. The fact of widespread theism is evidence for H. The strength of this evidence depends on how likely such belief would be if H were false.
  4. As people are more likely to do something if it makes them happy, people are more likely to be theists given F.
  5. Thus F opens up a way for people to be theists even if H is false.
  6. It therefore weakens the evidence of widespread theism for the truth of H.
  7. Therefore, F should decrease one's confidence in H, i.e., it is evidence against H.

We could also put this in mathematical terms, where F represents an increase in the prior probability of our encountering the evidence. Since that prior is a denominator in Bayes' equation, a bigger one means a smaller posterior probability--in other words, weaker evidence.

OK, so that was my first thought.

But then I had second thoughts: Perhaps the evidence points the other way? If we reframe the finding as "Atheism causes unhappiness," or posit that contrarians (such as atheists) are dispositionally unhappy, does that change the sign of the evidence?

Obviously, I am confused. What's going on here?