Tell me about CLT? What are the Parametric test and assumptions? Real life situation ?

Question

Accepted Answer

The Central Limit Theorem (CLT) states that the distribution of sample means approaches normality as sample size increases.

CLT applies to independent random samples from any population.
As sample size (n) increases, the sampling distribution of the mean becomes approximately normal.
For n ≥ 30, the sample mean is normally distributed regardless of the population's distribution.
Example: In quality control, measuring the average weight of products from a factory.
Parametric tests include t-tests and ANOVA, assuming normality and homogeneity of variance.