#StackBounty: #regression #regression-coefficients How to deal with various sample sizes in the calculation of a predictor variable?

Bounty: 50

Let’s say one of the predictor variables in a regression model is 3-point shooting percentage. However, some of the observations (players) only have one or two attempts while others have several more. In a regression model, what are some techniques so the ability demonstrated over a large number of attempts will be awarded a relatively larger magnitude value than in cases where there are less attempts?

For example…

Player      3PA 3PM 3P%
Player 2    174 52  29.9%
Player 3    156 64  41.0%
Player 4    4   3   75.0%
Player 5    134 45  33.6%

Player #4’s low sample size is not as reliable as the other observations but it’s not meaningless. Are there transformations or other techniques for handling this?


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