7.7 Random variability in baseball A baseball player in the major leagues who plays regularly will have about 500 at-bats (that is, about 500 times he can be the hitter in a game) during a season. Suppose a player has a 0.300 probability of getting a hit in an at-bat. His batting average at the end of the season is the number of hits divided by the number of at-bats. When we consider the 500 at-bats as a random sample of all possible at-bats for this player, this batting average is a sample proportion, so it has a sampling distribution describing where it is likely to fall.

a. Describe the shape, mean, and standard deviation of the sampling distribution of the player’s batting average.

b. Explain why a batting average of 0.320 or of 0.280 would not be especially unusual for this player’s year-end batting average. (That is, you should not conclude that someone with a batting average of 0.320 is necessarily a better hitter than a player with a batting average of 0.280. Both players could have a probability of 0.300 of getting a hit.)