A Z test is a type of hypothesis test Hypothesis testing is just a way for you

A z test is a type of hypothesis test hypothesis

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A Z-test is a type of hypothesis test. Hypothesis testing is just a way for you to figure out if results from a test are valid or repeatable. For example, if someone said they had found a new drug that cures cancer, you would want to be sure it was probably true. A hypothesis test will tell you if it’s probably true, or probably not true. A Z test, is used when your data is approximately normally distributed (Statistics how to, 2014).
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You would use a Z test if: Your sample size is greater than 30. Data points should be independent from each other. In other words, one data point isn’t related or doesn’t affect another data point. Your data should be normally distributed. However, for large sample sizes (over 30) this doesn’t always matter. Your data should be randomly selected from a population, where each item has an equal chance of being selected. Sample sizes should be equal if at all possible. How do I run a Z Test? Running a Z test on your data requires five steps: 1. State the null hypothesis and alternate hypothesis. 2. Choose an alpha level. 3. Find the critical value of z in a z-table.
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  • Spring '14
  • Epidemiology, Null hypothesis, Statistical hypothesis testing, Non-parametric statistics, Spearman's rank correlation coefficient

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