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Finding & Using Data

Are you looking for data or statistics?

Do you need a fact, facts or a number? You likely need statistics. Do you need to do an analysis? You need a dataset.


Data: Fundamentally, data is information. However the term data typically refers to numeric files that are created and organized for analysis. There are two types of data:

  • Aggregate data: statistical summaries of data, meaning the data have been analyzed in some way.  
  • Microdata: Individual response data obtained in surveys and censuses - these are data points directly observed or collected from a specific unit of observation. Also known as raw data. 

Data point: Singular of data. Refers to a single point of data.

Indicator: Typically used as a synonym for statistics that describe variables that describe something about the socioeconomic environment of a society, eg, per capita income, unemployment rate, median years of education.

Statistic: A number that describes some characteristic or status of a variable, eg, a count or a percentage.

Statistics: Numerical summaries of data that has been analyzed in some way.

Variable: Any finding that can change or vary. Examples include anything that can be measured, such as the number of logging operations in Alabama.

Database: A collection of data organized for research and retrieval.

Types of Data

Quantitative data/Quantitative variables: Information that can be handled numerically.

Qualitative data/Qualitative variables: Information that refers to the quality of something. Ethnographic research, participant observation, open-ended interviews, etc., may collect qualitative data. Some element of the results obtained via qualitative research may be handled numerically, eg, how many observations, number of interviews, etc.

Time series data: Any data arranged in chronological order.

Longitudinal data: data that is collected repeatedly over a period of time, in which the same group of respondents are surveyed each time.

Discrete data: numeric data that have a finite number of possible values (1,2,3,4,5)

Continuous data: data that has an infinite number of possible values (1.4, 1.41, 1.414, etc.) 

Levels of Measurement

Nominal: Nominal data have no order and only gives names or labels to various categories (yellow, white, pink).

Ordinal: Ordinal data have order, but the interval between measurements is not meaningful (low, medium, high).

Interval: Interval data have meaningful intervals between measurements, but there is no true starting point (Fahrenheit temperature scale).

Ratio: Ratio data have the highest level of measurement. Ratios between measurements as well as intervals are meaningful because there is a starting point (Kelvin temperature scale).


Definition References: 

School of Data. School of Data Handbook. What is Data?; DATA-PLANET. Data and Statistics Terminology and Definitions

Calkins, K.G. Definitions, Uses, Data Types, and Levels of Measurement,

Data or Statistics Reference: Western Libraries. Data and Statistics