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Get Started with Data, Datasets, and Statistics

Are data, datasets, and statistics different?

Data and statistics are closely related and are often used interchangeably, but in research, they represent the different stages of understanding information.

Data refers to raw, unprocessed information or facts. It can come in various forms, such as numbers, text, images, or measurements. Imagine it as the building blocks of knowledge!

Datasets are structured collections of data points or observations. Think of it as a big table with rows (instances) and columns (variables). Datasets are like organized treasure troves of information!

Statistics are a collection of analyzed or classified data. It is what you get after making sense of the raw data. Think of a house made of building blocks!

Data
  • Raw information
    • Text
    • Numbers
    • Images
  • Unprocessed information captured from surveys, experiments, and observations

Examples:

  • Vote tallies in a school board election
  • Word use counts in fictional books from the 20th century
Datasets
  • Tabular datasets
    • Organized in tables with rows and columns
  • Time series datasets:
    • Sequential data collected over time
  • Image datasets:
    • Collections of images
  • Text datasets:
    • Textual data like reviews, articles, or interview responses

Examples:

  • Student grades with names, scores, and subjects
  • Stock prices over months
  • Weather data across days
  • Satellite images showing food deserts in specific cities
Statistics
  • Analyzed data
  • Visualizations such as charts and graphs
  • Items that reveal patterns, trends, and relationships within data
  • Percentages found in articles

Examples:

  • U.S. national debt since 1994
  • Monthly sporting event attendance by state

Do you need data or statistics?

Data and Statistics: Things to Consider

Flexibility and resourcefulness are essential when working with data and statistics.

  • Start with a clear topic. When choosing a research topic, be specific but also keep some flexibility. This allows you to adapt to the available data or statistics.
  • Understand the terminology. The terminology used for educational data or statistics differs from medical statistics. Be sure you know the correct terminology for the data or statistics you need.
  • Search by keywords. For example, to find literacy rates among women in a specific region, use the keywords "literacy" AND "female" and filter the results by geographic location.
  • Try browsing. Many sources for data or statistics include a browse feature.
  • Consider data availability challenges. Not all topics have readily available data or statistics, or it may not be in the format you need. Some data or statistics might be hidden behind paywalls or not collected at all. Be prepared to work with the information you can access and look at alternative sources.
  • Current data or statistics may be a year or more old. It takes time to gather and collate numbers.
  • Go to the source. If you find information in a research article but cannot locate it online or in the library, try requesting the data or statistics from the researcher. Check the article for the author's contact information or try their university's website.

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