1. Define the entries in the class data sheet as a population. Find the population mean and the population SD for the height variable (from the class data spreadsheet).

2. Create a sample mean and sample standard deviation for each of these 6 samples:

Sample 1: 59, 62, 67, 60;

Sample 2: 64, 72, 63, 66; Sample 3: 69, 72, 77, 67;

Sample 4: 55, 60, 62, 72;

Sample 5: 64, 62, 71, 69; Sample 6: 60, 62, 64, 66.

So by the end you should have 6 separate samples of 4 heights each, and each sample will have its own sample mean and sample SD.

3. Now lay out the population mean and your six sample means on an X axis, with all the sample means smaller than the population mean on the left of the population mean, and all the sample means larger than the population mean to the right of the population mean.

4. Then create an overall mean of the sample means (the mean of the distribution of sample means). Compare this mean to the population mean. Is this overall mean closer to the population mean than any of the specific sample means, and if it is, what does this tell us about the distribution of sample means?

5. Now create the SD of the distribution of the sample means (the standard error of M), using the following formula (G&W, pages 181-183): little sigma/ the square root of n (the sample size). If the sample size in this exercise was larger, what would happen to the standard error?

Attachment:- Class_data_spring_2016_1.rar