Common
Two-proportion Z-test
Statistical methods for comparing samples
Two-proportion Z-test
The two-proportion Z-test (also called the two-sample proportion Z-test) is a statistical hypothesis test for assessing whether two groups differ in the proportion of a binary outcome, in such a significant way that is beyond chance. For example, the proportion of patients responding positively to a treatment in a clinical trial versus control, the defect rate in quality control for two production lines, or the click-through rate in an A/B test of two alternative webpage designs. The test is appropriate when each observation is independent from another, can be classified as a success or failure (i.e., a Bernoulli trial) and the sample sizes are large enough that the sampling distribution of each sample proportion is well approximated by the central limit theorem. Under those conditions the observed difference of sample proportions can be converted to a standardized z-statistic (using a pooled standard error) and compared to the standard normal distribution to obtain p-values or form confidence...
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