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When will a t test be used instead of a Z test? Select one: a. When the population standard deviation is not known b. When the sample size is too large C. When the parameter to be tested is not the mean d. When the population mean is known

When will a t test be used instead of a Z test? Select one: a. When the population standard deviation is not known b. When the sample size is too large C. When the parameter to be tested is not the mean d. When the population mean is known

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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### Question: When will a t test be used instead of a Z test? #### Options: - **a.** When the population standard deviation is not known - **b.** When the sample size is too large - **c.** When the parameter to be tested is not the mean - **d.** When the population mean is known **Correct Answer:** a. When the population standard deviation is not known ### Explanation: In statistical analysis, a t test is typically used instead of a Z test when the population standard deviation is unknown and the sample size is small (usually less than 30). The t test is more robust in these situations because it accounts for the variability in the sample, providing a more accurate measure of statistical significance.
Transcribed Image Text:### Question: When will a t test be used instead of a Z test? #### Options: - **a.** When the population standard deviation is not known - **b.** When the sample size is too large - **c.** When the parameter to be tested is not the mean - **d.** When the population mean is known **Correct Answer:** a. When the population standard deviation is not known ### Explanation: In statistical analysis, a t test is typically used instead of a Z test when the population standard deviation is unknown and the sample size is small (usually less than 30). The t test is more robust in these situations because it accounts for the variability in the sample, providing a more accurate measure of statistical significance.
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