As exceptional performance is difficult to maintain over time, there is a high chance of worse performance in the next quarter, shifting the performance of the company back towards the mean. Suppose that a company has a great quarter, exceeding all targets set. In general, RTM explains why unusual events are likely to be followed by more typical ones. Regression to the mean is observed when variables that are extremely higher or extremely lower than average on the first measurement move closer to the average on the second measurement. Calculating the percent of regression to the mean.Why is regression to the mean a problem?.It is considered a type of information bias and can distort research findings. Regression to the mean is common in repeated measurements ( within-subject designs) and should always be considered as a possible cause of an observed change. In other words, due to RTM, a great performance is more likely to be followed by a mediocre one than another great one, giving the impression that appearing on the cover brings bad luck. But athletic success is a mix of skill and luck, and even the best players don’t always win.Ĭhances are that good luck will not continue indefinitely, and neither can exceptional success.
Players or teams featured on the cover of SI have earned their place by performing exceptionally well. Example: Regression to the meanRegression to the mean can explain the so-called “ Sports Illustrated jinx.” This urban legend claims that athletes or teams that appear on the cover of the sports magazine will perform poorly in their next game. It is sometimes also called regression toward the mean. It can be observed in everyday life, particularly in research that intentionally focuses on the most extreme cases or events. Regression to the mean is due to natural variation or chance. Regression to the mean (RTM) is a statistical phenomenon describing how variables much higher or lower than the mean are often much closer to the mean when measured a second time.
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