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