overview of the One Sample Z-Test
One Sample Z Test is used to test if the sample studied follows a normal distribution, assuming that the standard deviation and mean are known. The mean is equal to the test value based on the sample drawn.
Cases where standard deviations are known are rare; a more common method of test in that case is the One Sample T Test.
Requirements for using One Sample Z Test:
Here, the goal is to test the hypothesis that the population where the sample is drawn from follows a normal distribution with the mean equal to the value that is set.
The population studied is assumed to follow a normal distribution.
The standard deviation of the population is already known.
The formula is:
where X is the sample, μ0 is the test value of mean, σ is The known standard deviation, and N is the sample size.
When the sample size, N, is sufficiently large, Z is approximately Normal⁡0,1.
After a math exam, Professor Lee marked and recorded down the grades of 100 students randomly selected from the entire group of 1000 students. It shows that their average grade is 65.
He has reasons to assume the grades are normally distributed with standard deviation equal to 15. Now he wants to test if the grades of all students follow a normal distribution whose mean is 64.5.
Determine the null hypothesis:
Null Hypothesis: μ0=64.5 (the actual mean).
Substitute the information into the formula:
z⁢=⁢65−64.515100 = 0.333333
Compute the p-value:
p−value=Probability(|Z|⁢>⁢0.333333)=⁢ProbabilityZ⁢<⁢−0.333333⁢+⁢ProbabilityZ⁢>⁢0.333333= 0.738883 Z⁢˜⁢Normal0,1.
Draw the conclusion:
This statistical test does not provide enough evidence to conclude that the null hypothesis is false, so we fail to reject the null hypothesis.
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