What is the difference between sample variance and sampling variance? They seem same. Aren’t they?
Sample variance refers to variation of observations (the data points) in a single sample. Sampling variance refers to variation of a particular statistic (e.g. the mean) calculated in sample, if to repeat the study (sample-creation/data-collection/statistic-calculation) many times. Due to central limit theorem, though, for some statistics you don’t have to repeat the study many times in reality, but can deduce sampling variance from a single sample if the sample is representative (this is asymptotic approach). Or you could simulate repetition of the study by a single sample (this is bootstrapping approach).
An additional note on “sample variance”. Two may be mixed in one term:
Estimate of population variance based on this sample. This is what we
usually use, it has denominator (degrees of freedom) n-1.
Variance of this sample. It has denominator n.