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Z-test
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<p>A <i>Z</i>-test is any <a href="/facts/Statistical_hypothesis_testing/yv9RPF6U">statistical test</a> for which the <a href="/facts/Probability_distribution/EpsKKVRu">distribution</a> of the <a href="/facts/Test_statistic/IBwfN5Kx">test statistic</a> under the <a href="/facts/Null_hypothesis/C8NwSE9J">null hypothesis</a> can be approximated by a <a href="/facts/Normal_distribution/UapjjPyQ">normal distribution</a>. <i>Z</i>-test tests the mean of a distribution. For each <a href="/facts/Statistical_significance/PMxjdlAu">significance level</a> in the <a href="/facts/Confidence_intervals/NS8mG5UE">confidence interval</a>, the <i>Z</i>-test has a single critical value (for example, 1.96 for 5% two-tailed), which makes it more convenient than the <a href="/facts/Student%2527s_t-test/dMH8uC28">Student's <i>t</i>-test</a> whose critical values are defined by the sample size (through the corresponding <a href="/facts/Degrees_of_freedom_(statistics)/fvwKCU86">degrees of freedom</a>). Both the <i>Z</i>-test and Student's <i>t</i>-test have similarities in that they both help determine the significance of a set of data. However, the <i>Z</i>-test is rarely used in practice because the population deviation is difficult to determine. </p>