Data – Raw facts and numbers collected for analysis.
Information – Data that has been organized and structured.
Knowledge – Understanding gained from interpreting data.
Nominal Data – Data that identifies or labels (e.g., country names).
Categorical Data – Grouped nominal data (e.g., political party affiliation).
Ordinal Data – Data with a meaningful order but unknown differences (e.g., rank).
Interval Data – Numeric data with a fixed unit but no meaningful zero (e.g., temperature).
Ratio Data – Numeric data with a meaningful zero, allowing for ratios (e.g., income, population).
Classification – Grouping data into classes for easier interpretation.
Equal Interval Classification – Divides data into equal-sized ranges.
Quantile Classification – Groups data so that each class contains the same number of values.
Natural Breaks (Jenks) – A statistical method that places class breaks where data naturally clusters.
Standard Deviation Classification – Classifies data based on how much it deviates from the mean.
Geometric Interval Classification – Each class is larger than the previous by a fixed ratio.
Manual Classification – The mapmaker sets class breaks based on meaningful thresholds.
Normalization – Adjusting data values to account for area or population size.
Dot Density Map – A map where dots represent quantities, used for ratio data.
Proportional Symbol Map – Symbols (e.g., circles) that scale in size based on data values.
Choropleth Map – A map where areas are shaded based on data values.
Mixed Symbol Map – A map that combines multiple visualization techniques.
Modifiable Areal Unit Problem (MAUP) – Changes in geographic unit size or boundaries can alter data interpretation.
Enumeration Unit – The geographic area in which data is grouped (e.g., state, county).
Observation Unit – The smallest level at which data is collected (e.g., individuals in a census).