Categorical Data
Categorical
Quantitative
Discrete
Continuous
Values that are category names or group variables
Show frequencies or relative frequencies that observations fall into each category
Numerical values for a measured or counted quantity
Can be used for mathematical operations
A countable number of values
Can take on infinitely many values
Pie (circle) charts- categories in relation to a whole
Bar graphs/charts- categories in relation to each other
Side-by-side bar graphs- bars are grouped together and placed side by side
Segmented bar graphs- displays variable distribution as segments in a rectangle
Mosiac plots- a three-way split of data structured like a segmented bar graph
Two categorical variables can be summarized in a two-way table
Gives counts of observations for each combination of variables
Each cells percentage of the total (in a table)
Focuses on only one categorical variable
Row and column totals for a two-way table
Relative frequency for specific row or column
When one variable helps to predict the other
Categorical
Quantitative
Discrete
Continuous
Values that are category names or group variables
Show frequencies or relative frequencies that observations fall into each category
Numerical values for a measured or counted quantity
Can be used for mathematical operations
A countable number of values
Can take on infinitely many values
Pie (circle) charts- categories in relation to a whole
Bar graphs/charts- categories in relation to each other
Side-by-side bar graphs- bars are grouped together and placed side by side
Segmented bar graphs- displays variable distribution as segments in a rectangle
Mosiac plots- a three-way split of data structured like a segmented bar graph
Two categorical variables can be summarized in a two-way table
Gives counts of observations for each combination of variables
Each cells percentage of the total (in a table)
Focuses on only one categorical variable
Row and column totals for a two-way table
Relative frequency for specific row or column
When one variable helps to predict the other