Title: Associations between 2 variables - Summary
Course: UGQuants (SSPS) > Section: Associations Between 2 Variables

Associations between 2 variables - Summary

In this module you should have learned the following:

1 | How to tell apart the independent and the dependent variable based on your theoretical assumptions. Independent variables can also be called explanatory variable, because they are used to explain the variation of data in the dependent variable.
2 | That crosstabs (or contingency tables) are useful when you explore whether two (or more) variables are associated with each other.
3 | In crosstabulations, the independent variable is commonly placed in the columns and the dependent in the rows.
4 | When to use column percentages and when row percentages.
5 | To follow good table manners, such as clear labeling, providing a good title, the data source and the sample size.
6 | That crosstabs only work well for nominal and ordinal variables (also called 'categorical variables').
7 | When checking for an association between categorical and ratio variables, comparing means or other measures of distribution is more helpful.