1. STATISTICS ELEMENTARY MARIO F. TRIOLA
Section Design of Experiments
MARIO F. TRIOLA
EIGHTH
EDITION

2. Definitions Observational Study Experiment
observe and measure specific characteristics without attempting to modify the subjects being studied
Experiment
apply some treatment and then observe its effects on the subjects
page 17 of text

3. Designing an Experiment
Identify your objective
Collect sample data
Use a random procedure that avoids bias
Analyze the data and form   conclusions

4. Definitions Confounding
occurs in an experiment when the effects from two or more variables cannot be distinguished from each other

5. Definitions Replication
repeating an experiment on a different sample (generally a larger sample, so that the we can see the true nature any effects and not be misled by erratic behavior of samples that are too small).

6. Definitions Random Sample Simple Random Sample (of size n)
members of the population are selected in such a way that each has an equal chance of being selected
Simple Random Sample (of size n)
subjects selected in such a way that every possible sample of size n has the same chance of being chosen

7. Random Sampling - selection so that each has an equal chance of being selected
page 19 of text

8. Systematic Sampling - Select some starting point and then select every K th element in the population

9. Convenience Sampling - use results that are readily available
Hey!
Do you believe
in the death
penalty?

10. Stratified Sampling - subdivide the population into subgroups that share the same characteristic, then draw a sample from each stratum

11. Cluster Sampling - divide the population into sections (or clusters); randomly select SOME of those clusters; choose ALL members from selected clusters
Students will most often confuse stratified sampling with cluster sampling. Both break the population into strata or sections. With stratified a few are selected from each strata. With cluster, choose a few of the strata and choose all the member from the chosen strata.

12. Methods of Sampling Random Systematic Convenience Stratified Cluster
review of the 5 different types of sampling

13. Definitions Sampling Error Nonsampling Error
the difference between a sample result and the true population result; such an error results from chance sample fluctuations.
Nonsampling Error
sample data that are incorrectly collected, recorded, or analyzed (such as by selecting a biased sample, using a defective instrument, or copying the data incorrectly).
page 23 of text