1. Unit 1: Producing Data

2. 1.1: Sampling – Good & Bad Methods Define sampling methods. Interpret the use of different sampling methods for different scenarios.

3. Definitions Sampling Method: Voluntary Response:

4. Example 1

5. Definitions Convenience Sampling:

6. Example 2

7. Definitions Bias: Bad Sampling Methods: Voluntary response Convenience

8. Definitions Good Sampling Methods Systematic Random Sample______________________

9. Use a table or your calculator to generate random integers.

10. Example 3

11. Definitions

12. Example 4 Stratified Random Sample Suppose you needed to sample the students at your school. Instead of randomly choosing students who walk through the door, you could divide them by grade level (strata) and randomly choose a number of students from each that is proportional to that groups representation in the total school population. This would give you a more representative sample of the schools population.

13. Definitions

14. Example 5

15. Definitions Multistage Sampling Design: A complex form of cluster sampling. Cluster sampling is a type of sampling which involves dividing the population into groups (or clusters). Then, one or more clusters are chosen at random and everyone within the chosen cluster is sampled. Using all the sample elements in all the selected clusters may be prohibitively expensive or not necessary. Under these circumstances, multistage cluster sampling becomes useful. Instead of using all the elements contained in the selected clusters, the researcher randomly selects elements from each cluster. Constructing the clusters is the first stage. Deciding what elements within the cluster to use is the second stage. The technique is used frequently when a complete list of all members of the population does not exist and is inappropriate.

16. Homework 5.2, 5.6, 5.7, 5.9, 5.11, 5.24, 5.32