00:01
Let's have a look on the question.
00:01
So here in this question, we need to describe three aspect of clt and why clt is used in empirical research.
00:09
Clt which means central limit theorem, central limit theorem is commonly defined as a statistical theory that give that given given a sufficiently large sample size, sufficiently large sample size from a population, from a population with a finite level of variance, with the finite level of variance, the mean of all samples, the mean of all samples from the same population will be, from the same population will be approximated, approximated equally or equal to the mean of the population, to the mean of the population.
01:45
So here in other words, we can say that if we have any finite population given any sufficiently large sample size and finite level of variance, so the mean of all samples from the sample population will be approximated equal to the mean of population and as sample size increases, sample size increases the sampling distribution of mean, the sampling distribution of the mean can be approximate by a normal, can be approximated by a normal distribution with mean mu, with mean mu and standard deviation sigma and standard deviation sigma divided by under root of n, where mu represents mu is equal to mean, then we have sigma is equal to population standard deviation, population standard deviation...