Often, novice researchers improperly interpret **odds ratios** as *probabilities*—this is wrong. The “odds” of an outcome occurring is a *ratio of successes to failures. * For example, an odds of 1.00 would correspond to a probability of 0.50. *Odds ratios*, then, reflect the predicted change in the odds given a 1 unit change in the predictor. That is, the odds ratio reflects change relative to the base odds of the outcome occurring. Given an outcome that either rarely occurs or almost always occurs, a *small* change in probability can correspond to a *large* odds ratio. Odds ratios are a ratio of ratios which can be quite confusing!

Because of this confusion, you will need to study the interpretation of odds ratios in depth. You will also need to be able to explain them to a nontechnical audience. In other words, we need to be able to translate statistical software output into an intuitive way to understand your research results. Much of social research has policy and practice implications. Practitioners may not understand the idea of an odds ratio. In an academic writing context, this means that you’ll provide a table of odds ratios for your sophisticated readers, but you’ll also want to provide an intuitive understanding in your conclusions.

Last Modified: 02/14/2019