In logistic regression, there are three terms that are used frequently but can be confusing if they are not thoroughly explained. These three terms are probability, odds, and odds ratio. In this post, we will look at these three terms and provide an explanation of them.

**Probability**

Probability is probably (no pun intended) the easiest of these three terms to understand. Probability is simply the likelihood that a certain event will happen. To calculate the probability in the traditional sense you need to know the number of events and outcomes to find the probability.

Bayesian probability uses prior probabilities to develop a posterior probability based on new evidence. For example, at one point during Super Bowl LI the Atlanta Falcons had a 99.7% chance of winning. This was base don such factors as the number points they were ahead and the time remaining. As these changed, so did the probability of them winning. yet the Patriots still found a way to win with less than a 1% chance

Bayesian probability was also used for predicting who would win the 2016 US presidential race. It is important to remember that probability is an expression of confidence and not a guarantee as we saw in both examples.

**Odds**

Odds are the expression of relative probabilities. Odds are calculated using the following equation

^{probability of the event }⁄ _{1 – probability of the event}

For example, at one point during Super Bowl LI the odds of the Atlanta Falcons winning were as follows

^{0.997 }⁄ _{1 – 0.997 = 332}

This can be interpreted as the odds being 332 to 1! This means that Atlanta was 332 times more likely to win the Super Bowl then loss the Super Bowl.

Odds are commonly used in gambling and this is probably (again no pun intended) where most of us have heard the term before. The odds is just an extension of probabilities and they are most commonly expressed as a fraction such as one in four, etc.

**Odds Ratio**

A ratio is the comparison of two numbers and indicates how many times one number is contained or contains another number. For example, a ration of boys to girls is 5 to 1 it means that there are five boys for every one girl.

By extension odds ratio is the comparison of two different odds. For example, if the odds of Team A making the playoffs is 45% and the odds of Team B making the playoffs is 35% the odds ratio is calculated as follows.

^{0.45 }⁄ _{0.35 = 1.28}

Team A is 1.28 more likely to make the playoffs then Team B.

The value of the odds and the odds ratio can sometimes be the same. Below is the odds ratio of the Atlanta Falcons winning and the New Patriots winning Super Bowl LI

^{0.997}⁄ _{0.003 = 332}

As such there is little difference between odds and odds ratio except that odds ratio is the ratio of two odds ratio. As you can tell, there is a lot of confusion about this for the average person. However, understanding these terms is critical to the application of logistic regression.