In this module you will practice using the statistics associated with the distribution of sample means. Remember that in the previous chapters, we have focused on statistical procedures for populations where we knew all of the individual scores. In Chapter seven we are using distributions of sample means and extending what we have learned about the normal distribution and probability to the sampling distribution of means. These concepts are reviewed in the textbook and lecture for Chapter 7. There is no SPSS component to this module. *You will need a copy of the unit normal table to complete this module.

1. Describe Sampling Error

2. Under which two conditions will the shape of the distribution of sample means be almost perfectly normal?

3. For samples selected from a population with = 100 and =8, which of the following has the smallest standard error? Samples: n = 5, n = 16, or n = 24. Explain your answer.

4.A sample of n = 100 scores is selected from a population with = 80, and = 20. On average, how much error is expected between the sample mean and the population mean?

5. Suppose you have a normal distribution: = 150 and = 24. Compute the standard error of M for a sample of 64.

6. A normal population has = 200 and = 20. A random sample of n = 25 scores from this population has a mean of 190. What is the z-score for this sample mean? What is the probability of getting a score lower than 190? Please draw the z-score on the normal curve and shade the proportion of interest.

7. A sample of n=16 scores is selected from a normal distribution with a= 40 and a standard deviation of= 21. The sample mean isM= 45. Find the z-score for this sample mean and determine the probability of obtaining a sample mean larger thanM=45. Please draw the z-score on the normal curve and shade the proportion of interest. answer these questions