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Both Z-test and T-test are statistical hypothesis tests. The Z-test is a statistical test used to determine whether two population means are different when the variances are known, and the sample size is large, the standard deviation is unknown while z-tests assume that it is known. Z-test has a single critical value which makes it more convenient than the t-test which has separate critical values for each sample size. A T test is normally used to test the mean of one population against its standard deviation. It can also be used to compare means of two population.
1. Z-test is a statistical hypothesis test that follows a normal distribution while T-test follows a Student’s T-distribution.
2. A T-test is appropriate when you are handling small samples (n < 30) while a Z-test is appropriate when you are handling moderate to large samples (n > 30).
3. T-test is more adaptable than Z-test since Z-test will often require certain conditions to be reliable. Additionally, T-test has many methods that will suit any need.
4. T-tests are more commonly used than Z-tests.
5. Z-tests are preferred than T-tests when standard deviations are known.
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