Imagine you are the coach of an NBA team. You have the opportunity to sign one of the two current superstars of the league. The two players have basically the same characteristics whether physical or actual game statistics. They have the same age, height, weight, wingspan, average points, rebounds, assists, steals, and blocks per game. Their only difference lies in the standard deviations for their points per game. Player 1 has a standard deviation of 5 while Player 2 has a standard deviation of 10. Who would you sign and why?
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
Imagine you are the coach of an NBA team. You have the opportunity to sign one of the two current superstars of the league.
The two players have basically the same characteristics whether physical or actual game statistics. They have the same age, height, weight, wingspan, average points, rebounds, assists, steals, and blocks per game.
Their only difference lies in the standard deviations for their points per game. Player 1 has a standard deviation of 5 while Player 2 has a standard deviation of 10.
Who would you sign and why?
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