35. This is used to determine the probability of an event by transforming the mean of the sample to a variable of this distribution where the population variance is unknown, and the sample size is less than 30. A. Z-Distribution C. Chi-Square Distribution D. Pearson Correlation Coefficient B. t-Distribution 36. Given u = 15, o = 5, and n = 50. This is an example of the sampling distribution of the sample mean for a normal population when the population variance is A. unknown C. large D. small B. known

MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Chapter1: Starting With Matlab
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35. This is used to determine the probability of an event by transforming the mean of the
sample to a variable of this distribution where the population variance is unknown, and the
sample size is less than 30.
A. Z-Distribution
C. Chi-Square Distribution
D. Pearson Correlation Coefficient
B. t-Distribution
36. Given u = 15, o = 5, and n = 50. This is an example of the sampling distribution of the
sample mean for a normal population when the population variance is
C. large
%3|
A. unknown
B. known
D. small
Transcribed Image Text:35. This is used to determine the probability of an event by transforming the mean of the sample to a variable of this distribution where the population variance is unknown, and the sample size is less than 30. A. Z-Distribution C. Chi-Square Distribution D. Pearson Correlation Coefficient B. t-Distribution 36. Given u = 15, o = 5, and n = 50. This is an example of the sampling distribution of the sample mean for a normal population when the population variance is C. large %3| A. unknown B. known D. small
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