Chapter 6: 12 October 2006

We continued our discussion on sampling distributions. We saw four important points:

1. The average of all the sample means is equal to the population mean μ. That is, E(Xbar) = μ
2. The variance of the sample mean is equal to the variance of the population divided by the sample size. That is, σ²_xbar= σ²/n.
3. When the population is normally distributed, the sample mean distribution is also normal. That is, if X ~ N, Xbar ~ N.
4. When we don't know the distribution of the population, the distribution of the sample mean is approximately normally distributed for large sample sizes. This is called the central limit theorem.

Section 001
Section 002