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Keep Calm and Become Data Savvy

This workshop will help you fill in the context that makes numerical data and statistics more than something to skip over or run away from.

What is Data?

  • "facts and statistics collected together for reference or analysis" (Oxford Dictionary of English, 3rd ed.)
  • "facts or information used usually to calculate, analyze, or plan something; information that is produced or stored by a computer" (Merriam-Webster Dictionary online)
  • "The evidence as a basis for analysis, policy, or practice. Data can be quantitative or qualitative." (Oxford Dictionary of Human Geography)
  • "A collection of facts or organized information, usually the results of observation, experience, or experiment, or a set of premises from which conclusions may be drawn. Data may consist of numbers, words, or images." (Oxford Dictionary of Dentistry)
  • "(research) Any material recorded from empirical research (see data gathering) from which inferences may be made, using some form of data analysis, in order to provide information." (Oxford Dictionary of Media and Communication)

Data or Statistics?

The two terms are often used interchangably. Although there are some commonly understood distinctions, there are also grey areas: statistics are certainly a kind of data, and data are used to generate statistics. 

Statistics often are:

  • facts or figures
  • time series
  • tables, charts, or graphs
  • to support an argument
  • 'ready to use'

Data can generally be used to:

  • test hypotheses
  • generate custom tables
  • look at responses of individuals
  • analyze in SPSS, SAS, or Stata
  • do Regression, t-test, ANOVA, etc
Another distinction to consider is whether you need microdata or aggregate data. Microdata is the original, unprocessed (except to protect privacy of participants) information: for example, income reported by each household, height and species of each tree in a park. Aggregate data is summarized and combined in some way: average income in a census block, number of oak trees in a city park.

Becoming Data Savvy

What does it mean to be "data savvy"?

A data savvy individual is someone who is data literate - who can "access, interpret, critically assess, manage, handle and ethically use data" (Prado & Marzal, 2013).

But I don't want to be a data scientist!

Don't panic - you don't have to.