Two-way Tables

conditional distribution

- break down one group by other variable - used to compare groups

marginal distribution

- distribution of one variable with overall results - does not consider any information from another variable

joint "and" distribution

- overall percentage in each cell - sums to one

you can compare two marginal distributions to see if the corresponding two variables are related

false

if variables A and B are related in a certain way in a two-way table, not matter how many other variables you look at in addition to these two, the relationship will...

not always stay the same

if conditional distributions of x and y are the same...

they are not related (no relationship)

if conditional distributions of x and y are the different...

they are related (relationship)

a two-way table has this name because it contains rows going one way and columns going the other way

true

two-way tables explore relationships between...

two categorical variables

Simpson's paradox

when a two-way table shows one relationship, but the relationship reverses if a third variable gets involved