Research Guides: Finding Data: Home

Introduction

What is the difference between statistics and data? Sometimes the two words are used interchangeably when they are two different things.

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When looking for data, clearly define what data you need. Ask yourself questions about the type of data you are looking for.
Before conducting research with human subjects, you must receive approval from your school's Institutional Review Board (IRB) to ensure information is kept confident and/or anonymous.
Before analyzing data, determine the level of measurement associated with the data - nominal, ordinal, interval, or ration.
When visualizing data, be sure axes and keys are labeled; colors are logical, distinguishable, accessible, and necessary; keep in mind your intended audience; and be aware of conscious and preconscious judgments.

DMPTool
The Data Management Plan (DMP) Tool helps generate data management plans based on the requirements of various funding agencies, both federal and private funding sources.

ICPSR This link opens in a new window
The Inter-university Consortium for Political and Social Research (ICPSR) maintains and provides access to an archive of social science data for research and instruction, and offers training in quantitative methods to facilitate effective data use. Auraria campus users (faculty, staff, students) must register for a personal ICPSR account from an on-campus, networked computer (or a VPN connection) to be able to download data.

Data.gov
Data.gov increases the ability of the public to easily find, download, and use datasets that are generated and held by the Federal Government.
Denver Open Data
Open data about all aspects of Denver including transportation, population, buildings, public works, etc.

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.

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