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@jemoka / Jemoka Knowledge Base / wiki/concepts/z_test.md
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--- title: "z-test" type: concept related: [Z Test, Test For Normality, Hypothesis Testing] source: https://www.jemoka.com/posts/kbhz_test/ confidence: high status: active --- A z-test is a hypothesis test for statistical significance between two sample proportions. Before it can be conducted, it must meet the conditions for inference for a z-test. conditions for inference (z-test) has to be random has to be reasonably normal (vis a vi test for normality) each sample has to be independent (or 10% rule) use a z-statistic to find p-value Given a sample proportion, calculate the sample proportion standard deviation (given on the formula sheet) Then, divide the difference between measured and null proportions to figure \(z\) that is, \begin{equation} z = \frac{\hat{p}-p_0}{\sqrt{\frac{p_0(1-p_0)}{n}}} \end{equation} Look up the probability of \(z\) taking place on a \(z\) table. Then, \(1-z\) would yield the \(p\) vaule.