Data: Finding, Interpreting, and Managing Data: Home

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

• Data is the raw information from which statistics are created.  
• Statistics provide an interpretation and summary of the data.  

This guide is organized by the order in which data resources are collected and used.

• Find Data: Find a data set to use.
• Collect Data: For those who want to collect their own data, learn where and how to collect data including methods of data collection and what software to use.
• Manage Data: Ensure your data is stored and managed properly.
• Analyze Data and Statistics: This is primarily done through statistical analysis software. Includes information on the different software.
• Visualize Data: Visually represent the data to share with others.
• Data Science: This is a broad term for working with different types of data. Different data types include big data and data mining.

• 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.

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.