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Z-test and T-test are statistical tests used to determine whether two population means are different. Z- test is applied 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. T-tests are more commonly used than Z-tests. A T-test is appropriate when you are handling small samples while a Z-test is appropriate when you are handling moderate to large samples. Z-test is a statistical hypothesis test that follows a normal distribution while T-test follows an individual’s T-distribution. T-test is more adaptable than Z-test since Z-test will often require certain conditions to be reliable.