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Quantitative variable
represents numerical values that make sense to perform mathematical operations like addition or multiplication
“how many?” “how much”
ex: age, height, # of pets
Categorical variable
Values that represent groups, labels, or qualities. They sort data into distinct categories. It doesn’t make sense to perform numerical operations on these values.
ex: eye color, marital status (divorced, married), brand of a product (nike, adidas), fav movie genre (horror, comedy).
proportion
value that represents a fraction of a whole. its a way of summarizing data by showing the part of the group with the same characteristic.
ex: 100 students, 60 like comedy ; proportion of students who like comedy are 60/100 OR 0.60
Relative Frequency Distribution
shows the percentage/proportion of times each value or category appears.
ex: 50 people have brown hair, 30 blonde hair, 20 black hair.
Brown hair: 50/100 =0.5 or 50%
Blonde hair: 30/100=0.3 or 30%
Black hair: 20/100=0.2 or 20%