POLS 3650 Lecture Notes - Lecture 5: Missing Data

• School: University of Guelph
• Department: Political Science
• Course: POLS 3650
• Professor: Edward Koning

Document Summary

Sometimes nominal variables are called qualitative variables and other variables (ordinal, interval, ratio) quantitative variables. It is common to treat ordinal variables as interval/ratio variables if the number of possible values is large (at any rate higher than 5) Dichotomous (or binary) variable: a variable that can only assume two values. E. g. cat owner (no/yes), income (poor/rich), voted (no/yes) Dichotomous variables can always be treated as ratio variables as long as their values are. Every step has the same distance (because there is only one step) There is a natural zero point (the complete absence of the variable) We can make a further distinction among interval & ratio variables. Continuous variables can assume any possible non-integer value (decimal). Are always quantitative: e. g. age of a basketball player. He is 25 years old -> 25. He is 25 years and 6 months old -> 25. 5. He is 25 years, 6 months, and 4 days old -> 25. 512.