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Finding Data: Home

Finding, interpreting, and managing data


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.  


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Best Practices

  • 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.

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Types of Data

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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