Data and Statistics

Welcome! This guide will introduce you to:

• Different types of data
• Where to find data and statistics
• Considerations around data
• Campus resources

Data are used regularly in everyday life. You may use:

• Weather information to plan your day
• Rating information to choose (or not choose) a particular product or restaurant
• A smartwatch to tell you how well you did (or didn't) sleep or to count how many steps you took
• A map app to find your way
• If you participate in research projects

You are also contributing data if you:

• Rate a restaurant
• Contribute to your map app (for example, clicking yes or no when it asks if a stalled vehicle is still there)
• Complete an online survey
• Use websites (they track your online activity)
• Contribute to social media
• Participate in citizen science projects
• If you participate in research projects

Research data, as defined in ODU Policy #5350: Research and Scholarly Digital Data Management Policy, is digitally recorded information that are necessary to support or validate a research project's observations, findings, or outputs.

It is recognized that the very concept of data can be complex and hard to define (Borgman, 2012). Data can mean different things to different people in different disciplines.

Any of the following could be considered data:

• Tables and spreadsheets
• Observations
• Surveys
• Interviews
• Transcripts
• Videos
• Audio
• Photographs, images, and art
• Models and simulations
• Software and code
• Geospatial information
• Archive materials

(Not an exhaustive list​. Adapted from NC State University Libraries Defining Research Data)

Keep in mind that although "data" and "statistics" are often used interchangeably, there is a difference.

• Statistics are a form of data, while data in "raw" form are not statistics.
• Statistics are data that have been analyzed or summarized in some way.
• Statistics are often presented in graphs or charts so you can visualize the data connections.

Watch this brief Data vs. Statistics: What's the Difference? video from ICPSR's #NoStupidQuestions series for an explanation.

Research is becoming more inter- and cross-disciplinary, but terminology can often be a challenge. Not only is different terminology used in different disciplines, but sometimes the same word means different things in different disciplines.

Examples:

• Coding: Some people's first thoughts may go to programming languages such as Python or R, while others may think of coding as defining themes in collected text or interviews.
• Instruments: Some people may think about physical tools, such as a microscope or a drone, while to others, a survey or questionnaire is also considered an instrument.

This Human Nature post When we're using the same words but mean different things reminds us there is no right or wrong terminology, but rather we need to be aware that words may have different meanings in different disciplines.