The National Football League (NFL) holds its annual draft of the nation's best college football players in April each year. Prior to the draft, various sporting news services project the players who will be drafted along with the order in which each will be selected in what are called mock drafts. Players who are considered to have superior potential as professional football players are selected earlier in the draft. Suppose the following table shows projections by one mock draft service of what position in the first round players from the Atlantic Coast Conference, the Big Ten Conference, the PAC-12 Conference, and the Southeastern Conference will be selected. ACC Big Ten PAC-12 SEC College Attended Projected Draft Position College Attended Projected Draft Position College Attended Projected Draft Position College Attended Projected Draft Position Florida State lowa USc 4 Florida 2 Clemson Michigan St 10 Oregon 6. Alabama Miami Nebraska 14 Oregon 15 Kentucky Georgia Tech 11 Minnesota 26 Washington 18 Texas ASM 12 Louisville 17 Wisconsin 27 UCLA 19 Missouri 13 Wake Forest 20 UCLA 22 Alabama 16 Florida State 21 Stanford 23 LSU 25 Virginia Tech 28 Arizona St 24 LSU 29 Use the Kruskal-Walis test to determine if there is any difference among NFL teams for players from these four conferences. Use a-0.0s. State the null and alternative hypotheses. H: The populations for the mock draft positions of the four conferences are identical. H: The populations for the mock draft positions of the four conferences are not all identical. H: The populations for the mock draft positions of the four conferences are not all identical. H: The populations for the mock draft positions of the four conferences are identical. H Medianace* Median O H Medianacc - Mediang Ten - MediangaC-12 " Mediangec O "g Ten * Hedanpac-12* Mediansee Hoi Medianace - Median Ten - MedianaC-12- Mediangee H,: Medianacc > Median Ten Mediangac-12> MediangeEC Ho: Medianacc - Mediang Tan- MedianpaAC-12 Median gec H: Medianacc Mediang Ten * MediangaC-12* Mediangec c
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.
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