CHILD DEVELOPMENT PEDAGOGY

Detailed explanation-1: -The central limit theorem (CLT) states that the distribution of sample means approximates a normal distribution as the sample size gets larger, regardless of the population’s distribution. Sample sizes equal to or greater than 30 are often considered sufficient for the CLT to hold.

Detailed explanation-2: -The general rule of thumb is that samples of size 30 or greater will have a fairly normal distribution regardless of the shape of the distribution of the variable in the population.

Detailed explanation-3: -Sample size and normality When the sample size is small, the sampling distribution of the mean is sometimes non-normal. That’s because the central limit theorem only holds true when the sample size is “sufficiently large.”

Detailed explanation-4: -If the population is normal, then the result holds for samples of any size (i..e, the sampling distribution of the sample means will be approximately normal even for samples of size less than 30).