Chapter 9

Risk and odds

1. Define the population risk of a negative outcome.
2. Define the population odds of a negative outcome.
3. Compute the sample risk and sample odds given a table summarizing positive and negative outcomes in a sample.

Chapter 20

Two-sample problems: proportions

1. Give examples of two-sample problems that involve proportions.

Relative risk and odds ratios

1. Define the population relative risk of a negative outcome in a treatment group compared to a control group.
2. Define the population odds ratio of a negative outcome in a treatment group compared to a control group.
3. Compute the sample relative risk and sample odds ratio given a two-way table.
4. State what value of relative risk / odds ratio corresponds to “no difference” in risk between the treatment and control populations.
5. Explain why relative risks and odds ratios are most appropriately considered on a logarithmic scale.
6. Recognize that odds are not risks, and odds ratios are not relative risks.
7. Interpret relative risks and odds ratios in terms of whether they indicate the treatment or control condition leads to lower risk.

Inferences for Relative Risks and Odds Ratios Using R (Lecture Notes for Lecture 24)

1. State the four conditions on the count of a categorical variable for it be binomial.
2. Compute the sample risks, relative risk, and odds ratio from a two-way table using oddsRatio from the mosaic package.
3. Compute confidence intervals for the population relative risk and odds ratio from a two-way table using oddsRatio from the mosaic package.
4. Use a confidence interval for either a population relative risk or population odds ratio to test for a difference in risk between a treatment and control population.