Today's lecture, or at least I tried to, was on Sampling Distributions. The idea behind sampling distributions is to understand the behavior of the sample mean. By doing that, we can then be able to predict the population mean more accurately. As an exercise, I asked each group to calculate the population mean (N=8). I then asked each group to take samples of size n=7, and for each sample, calculate the sample mean. You should have observed the following results:
The average of the sample means, i.e., E(Xbar) = μ, the population mean. In the next class, we will talk about other properties of the sampling distribution of the sample mean. Today's Section 001 lecture may be a little off the chart. Those who attended know why, I hope :-)
Section 001
Section 002
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