Qualitative Data: Non-numerical data. Examples: eye color, socioeconomic status
Quantitative Data: Numerical data. Examples: height, shoe size
Continuous Data: Continuous data can have an infinite number of values and therefore 0 is not meaningful. Examples: weight, height
Discrete Data: Discrete data has finite values and a meaningful 0. Example: number of people living in a household
Time-Series: Studying the same variable over time; the instrument is the same but different people will be used.
Longitudinal: Typically are surveys that are taken over time with the same people, but not always the same survey or instrument.
What is the difference between statistics and data? Sometimes the two words are used interchangeably when they are two different things.
This guide is organized by the order in which data resources are collected and used.