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1. Z-Test: Used when the sample size is large (typically n > 30) or when the population variance is known, to determine if there is a significant difference between sample and population means.


2. T-Test: Applied when the sample size is small (typically n ≤ 30) and the population variance is unknown, to compare means between groups or to test a sample mean against a known value.


3.Chi-Square Test: Used for categorical data to assess how likely it is that an observed distribution differs from a theoretical distribution, often applied in tests of independence or goodness-of-fit.

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. T-Test: Applied when the sample size is small (typically n ≤ 30) and the population variance is unknown, to compare means between groups or to test a sample mean against a known value.

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Z Test 
Chi square

T Test

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