Use the preparation materials to prepare hand-written answers for the following questions. Please ask any questions on the "Questions -- Preparation Guide" on the course Team (see link on the homepage.)
- Define “statistical inference.”
- Explain the primary difference between the way an experiment and an observational study are designed
- What is the primary difference between the types of conclusions that can be drawn from an experimental and observational study? Explain why this is the case.
- Within an experiment define: “factor”, “response”, “levels”, “treatments”, and “replicates.”
- How many numbers of levels must you list?
- How are the number of treatments determined from the number of levels?
- How are the number of replicates determined from the total number of individuals available for the experiment?
- Explain how you determine which individuals are placed into each treatment.
- Explain how you would use R (with the code) to determine which individuals are placed into each treatment.
- What are two advantages of an experiment that simultaneously manipulates two factors as compared to two separate experiments that each manipulate only one factor?
- What are three major principles of experimental design? Describe why each is important.
- What are three major types of observational studies? Describe each.
- What is a biased sample?
- How is a biased sample avoided?
- Which types of observational studies tend to produce a biased sample?
- Explain how individuals should be selected for a simple random sample.
- Explain how you would use R (with the code) to select individuals for a simple random sample.
- What are three reasons why an observational study is important, even though cause-and-effect statements cannot be made from one?
- What questions do you have from this reading that you would like me to address? [Please be as specific as possible. Don’t just say “everything” or “I don’t understand anything.” Of course, you can ask questions about the reading before class on MS Teams (see link above).]