Z-Test, T-Test, Chi-Square Test

. 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.

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.

Z Test 
Chi square

T Test