Divorce is one of those subjects that evokes significant emotion. Now that I am officially middle aged, the number of my friends and family that have had to suffer through divorce is growing. It is an event that no one plans for, but still happens at startling regularity. The interest in the state of failed marriages has led to a large amount of research on the topic. Unfortunately, lack of understanding of data has led to a large amount of misinformation.

If you have ever heard anyone mention divorce statistics in the news, church, or casual conversation you have likely been told that 50% of all marriages in the US end in divorce. Everyone who considers marriage is inevitably concerned with the likelihood of lifelong success. To this end, a simple percent statement of failure is easy to digest and understand. However, the divorce failure rate is incredibly misleading. Such a general statistic strips the nuance away from the truth of reality.

Pinning divorce rates into aggregate failure likelihood is an excellent example of bad data analysis. Social scientists that conduct formal studies do not use this metric, and prefer to measure divorce rates based on population (per 1000), or likelihood over a time horizon (i.e. 5 years). Stating an aggregate failure rate leads an individual to internalize the statistic and believe that it either directly applies to themselves or their circumstance writ large. It is clear that the 50% statistic is a sensational data point intended to influence belief about the condition of modern marriage. It creates a neat talking point inferring that marital success is left up to a coin flip.

Let me help dig into the actual raw divorce data (I have made the data available below for those that want to answer their own questions). Such data are collected both by the CDC and in peer-reviewed publications based on large surveys [1] [2]. I will focus only on the CDC data as it is authoritative.

This post could be called ‘why conditional probability is important’... but then no one would read it :). What I am going to show are a series of ‘conditions’ about divorce data that make aggregate interpretation misleading. The first, and most important, thing you need to know about divorce rates is that it greatly matters who you are. Specifically conditions of primary interest are your age at marriage, gender, education level, ethnicity, how many times you have been married and state of residence.

Let’s start with state of residence. Each state (with a few exceptions) reports two annual statistics to the CDC, marriage and divorce rates per 1000 people in the population. The two maps below show the marriage rates (left) and divorce/annulment rates (right) in each state.

Marriage Rates (left) and Divorce Rates (right) in 2012