POLS 3650 Lecture 3: Lecture #3 pols3650

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

Document Summary

Data, variables, & attributes: data: pieces of information that are subjected to analysis, variable: category" of characteristics in our data, variables take on different attributes (or values, variables vary from one case to another, example #1: Coding: for the purposes of quantitative data analysis, all values need to be coded (translated into numbers, codes are not identical, the codes attributed to the values of a variable can have different levels of measurements. Yes: nominal: all the codes tell us that there are different categories (values allow you to do something with a software, ordinal: our codes distinguish different categories but also rank them (give values". Practice question: at the end of each nhl match, three players are singled out as the best performers for the game. 3: in this class we will be dealing with ordinal variables with a large number of values. Dichotomous (or binary) variables: dichotomous (or binary) variable: a variable that can only assume two values.