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You may have heard that one-tailed or two-tailed z-tests are performed to determine whether an observed mean, mean difference or mean deviation is greater than or less than a given threshold or a pre-defined significance level. There are various types of z-tests including one-tailed, two-tailed, Bonferroni, Benford, Holm, and others. Each type has its own strengths and limitations. So, let us have a brief overview of the differences between one-tailed and two-tailed z-tests.
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One-tailed vs Two-tailed z-test Assignments As per the definition, we have two kinds of Z-test, which are “one-tailed Z-test” and “two-tailed Z-test” or “tail test”. Here’s the explanation: One-tailed Z-test: This z-test test the hypothesis that the mean value of a random sample from population is equal to a fixed value called the “measured mean”. It is considered to be a type of non-parametric test.
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One-tailed z-test: This is the classic z-test where the null hypothesis is a statement that one variable is significantly different from the rest of the sample variables. The alternative hypothesis is that all or most of the sample variables are significantly different from each other. The z-score represents the estimated difference between the means of the two groups. The result of the one-tailed z-test is the significance level (e.g. 5%). Two-tailed z-test: This is the opposite of the one-tailed
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