A pollster collects following data for 350 college students. Democratic Green Independent Republican Total Freshmen 20 30 25 30 105 Sophomore Junior 15 28 30 20 93 12 20 20 15 67 Senior 15 30 20 20 85 Total 62 108 95 85 350 Using MINITAB test the hypothesis that the voting patterns are similar across year in school. Use a = 0.05 %3D
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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