Chapter 5

Marginal distributions

1. Idenfity when a two-way table is appropriate for summarizing the relationship between an explanatory variable and a response variable.
2. Given a two-way table, compute the marginal distributions of the two-way table both as counts and percentages / proportions.
3. Identify what a marginal distribution, when given as a percentage or proportion, should sum to.

Conditional Distributions

1. Given a “word problem” asking for the proportion of individuals with one characteristic who have another characteristic, identify the appropriate numerator and denominator using a two-way table.
2. Explain why a conditional distribution is so-named.
3. Given a two-way table, compute the conditional distributions for one of the categorical variables as percentages / proportions.
4. Identify what a conditional distribution, when given as a percentage or proportion, should sum to.

Association versus Causation for Categorical Variables (Lecture Notes)

1. Distinguish between association and causation for categorical variables.
2. Posit potential “lurking variables” for an observed association between two categorical variables.