When you don't have the population standard deviation, but do have the sample standard deviation. The Z score will be better to do as long as it is possible to do it.
Because t-score isn't as accurate as z-score, you should use 40 as a safety sample size, rather than 30 as you would for a z-score.
The answer depends on what the test statistic is: a t-statistic, z-score, chi square of something else.
T-scores and z-scores measure the deviation from normal. The normal for T-score is 50 with standard deviation of 10. if the score on t-score is more than 50, it means that the person scored above normal (average), and vise versa. The normal for Z-score is 0. If Z-score is above 0, then it means that person scored above normal (average), and vise versa.
When the sample size is greater than 30
a t test is used inplace of a z-test when the population standard deviation is unknown.
The T-score is related to the Stiffness Index, because the Index is used to determine the T-score. This is an expression of structure, strength, and density.
Because t-score isn't as accurate as z-score, you should use 40 as a safety sample size, rather than 30 as you would for a z-score.
If we are testing a hypothesis about the population mean , if none of the conditions of using a z-score or the conditions for using a t-score are met, we may use a proper non-parametric test.
The answer depends on what the test statistic is: a t-statistic, z-score, chi square of something else.
T-scores and z-scores measure the deviation from normal. The normal for T-score is 50 with standard deviation of 10. if the score on t-score is more than 50, it means that the person scored above normal (average), and vise versa. The normal for Z-score is 0. If Z-score is above 0, then it means that person scored above normal (average), and vise versa.
T. J. Reddy has written: 'Less than a score, but a point'
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The"t" test, (called the "small 't' test, to distinguish it from the large 'T' test) is a test for deviation from a known norm, using a smaller sample set than the one required by the large T test. It is said to have been developed by the head of quality control at the Guinness Brewery in Ireland.
When the sample size is greater than 30
When the sample size is greater than 30
paired t-test is more powerful because it utilizes information
If you already have your p-value, compare it with 0.05. If the p-value is less than an alpha of 0.05, the t-test is significant. If it is above 0.05, the t-test is not significant.