# SOC222H5 Lecture Notes - Microbiology, Effect Size, Frequency Distribution

## Document Summary

Ratio is quantitative and all other categories are category. **today variables will either be nominal or ordinal: will have to variables, like male or female. Importance of the three types of bivariate relationships: the difference between causation and correlation, three criteria for causation. Terms to know independent variable dependent variable covariation descriptive statistics inferential statistics representative sample frequency distribution central tendency mode median crosstab effect size. Bivariate relationships x y- how we indicate this x causes y. Dependent vs. independent variable- depends, wearing them is effect of aging. Criteria: to say that x causes y: time order: x must come before y in time, that"s why sex is a determinant, if males make more money, you would say earnings determine sex. 2. covariation: x changes, y changes what ever happens is systematic. One variable varies with another variable, what stats focuses on: non-spurious: does x vary systematically with y,