What is the difference between a Z test, a Chi-Square test, a F test, and a T-test?

Data Science, AI and ML
#1

Z test is applied for large samples. Z test = (Estimated Mean – Real Mean)/ (square root real variance / n).

Chi-Square test is a statistical method assessing the goodness of fit between a set of observed values and those expected theoretically.

F-test is used to compare 2 populations’ variances. F = explained variance/unexplained variance.

T-test is applied for small samples. T-test = (Estimated Mean – Real Mean)/ (square root Estimated variance / n).