Regression To The Mean in Psychology: Definition & Example

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Lesson Transcript
Yolanda Williams

Yolanda has taught college Psychology and Ethics, and has a doctorate of philosophy in counselor education and supervision.

Expert Contributor
Jennifer Levitas

Jennifer has a Ph.D. in Psychology. She's taught multiple college-level psychology courses and been published in several academic journals.

Regression to the mean occurs when the second measurements of a particular variable are less extreme than the first. Learn about regression to the mean, random variance, and more.


Regression to the mean is a statistical phenomenon stating that data that is extremely higher or lower than the mean will likely be closer to the mean if it is measured a second time. This means that if you take two independent sets of measurements from every person in your sample, you would find that the people who had scores that were well above or below the mean during the first measurement would have scores that are closer to the mean in the second measurement.

Regression to the mean, also known as regression toward the mean, was discovered by Sir Francis Galton while he was conducting reporting the heights of 250 parents and their 930 children. Galton calculated the average height for the adults and children and plotted the heights of everyone on a chart. Galton found that parents who were taller than average tended to have children that were taller than average, and the parents who were shorter than average tended to have children who were shorter on average.

However, in instances where the parents were taller than average, the children tended to be a bit shorter than the parents, and in instances where the parents were shorter than average, the children tended to be a bit taller than the parents. In other words, the children of parents with heights that were extremely above or below average had heights that were closer to the average. Galton called this phenomenon regression of the mean.

Regression to the mean is due to random variance, or chance, which affects the sample. For example, part of height is due to our genes that we inherit from our parents, but there are also other random influences that may affect your height. It is the random variance that causes some of the samples to have extreme values. It is important to note that the random variance in the second measurement is not influenced by the random variance that affected the first measurement. Because of this, the samples will appear to regress on the second measurement.

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Regression to the Mean Writing Prompts

Writing Prompt 1:

For this assignment imagine that you give IQ and achievement tests as part of a process for children to apply to gifted schools. You tested one child and his IQ score was in the Very Superior range, in the top 1% of the population. You share the results with the parents, who are thrilled. In order to give their child the best possible application, they ask you to give the child another series of tests. You know that you cannot give the same tests within a year of administering them (due to practice effects), so you give similar but different tests. This time, the child tests in the Superior range, rather than in the Very Superior range. The parents are upset and baffled, wondering how their child's intelligence decreased within a few days. Write a paragraph or two on how you would explain this phenomenon to the parents based on regression to the mean. For example, you could explain what a mean is, what random variance is, and what happens to scores when they are either extremely high or extremely low (e.g., they move toward the mean).

Writing Prompt 2:

Have you heard of the "Sports Illustrated cover jinx?" This is the idea that once a person or sport's team appears on the cover of Sports Illustrated, they will be "jinxed" and have something bad happen afterward. For example, a football player may sustain an injury, a basketball player may start missing the hoop regularly, or a team on the winning streak may lose. Write two to three paragraphs explaining why this is not a jinx, but simple statistical regression to the mean. For example, a person who has made it on the cover of the sports magazine would have done so due to playing extremely well for a sustained period of time, which would increase the likelihood of injury.

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