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Z-test is a statistically significant test used to determine whether two population means are different from each other.

The test can be performed on one or two samples, or on proportions for hypothesis testing. It is used to test the null hypothesis, which states that the mean of a population is equal to a specific value. 

The Z-test is appropriate to use when the population standard deviation is known and the the sample size is large. It is based on the Z-score, which is the number of standard deviations a data point is from the mean. The test helps determine the significance of a set of data, determining the probability of a data point coming from a specific population. 

A one-sample z-test is calculated as follows:

two sample z-test for means formula and examples


x̄1, x̄2= the mean of samples first and second sample, 

μ1, μ2= the mean of  first and second population

σ1, σ2= the population standard deviation for first  and second population

n1 and n2= number of data points in first and second sample

Z-test is used for categorical features where number of labels is </= 2. The default threshold is 0.05 in AryaXAI.

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