# GGR270H1 Chapter Notes - Chapter 2: Central Tendency, Euclidean Distance, Spatial Analysis

## Document Summary

Nominal data: observations that have been placed into a set of mutually exclusive and collectively exhaustive categories: ex: soil type, vegetation type. Ordinal data: observations that are ranked, but not possible to say by how much an observation is greater or less than another: ex: ranking size of cities. Ratio data: does have a meaningful zero, can compare ratios. Discrete variables: only a finite set of values. C: ex: kelvin, number of sunny days in a year, temperature, altitude. 2: when number of observation is even, median is the average of the two middle values. Can have grouped means for data organized into categories (ex: income) G i=1 f i: weighted average, where the midpoint of each group is weighted by the frequency of observations in that group. After all these weighted quantities have been calculated and summed, divide by the sum of the weight: last category can be open-ended (ex: 500 and above)