| A | B |
|---|
| Frequency table/rel. freq. tbl. | lists the categories in a categorical variable and gives the count or percentage of observations for each category |
| Distribution | give the possible values of the variable and the rel. freq. of each value |
| Area Principle | In a stat. display, each data value should be represented by the same amount of area |
| Bar chart | show a ar representing the count of each category in a categorical variable |
| Pie chart | show how a "whole" divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category |
| Contingency table | displays counts and, sometimes, percentages of individuals fallinging into named categories on two or more variables. |
| Marginal distribution | In a contingency table, the distribution of either variable alone is called the marginal distribution. The counts or percentages are the totals found in the margins (last row or column) of the table. |
| Condtional distribution | The distributionj of a variable restricting the "who" ot consider only a smaller group of individuals is called a conditional distribution. |
| Independence | Variables are said to be independent f the conditionals distribution of one variable is the same for each category of the other. We'll show how to check for independence in a later chapter. |
| Simpson's paradox | When averages are taken across different groups, they can appear to contradict hte overall averages. This is known as "Simpson's paradox." |
