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Statistical Literacy & Data Literacy

Data literacy is the ability to locate statistics and data, and implies an understanding of data analysis.

Statistical literacy is the ability to understand and contextualize statistics and data.

You need both data literacy and statistical literacy to find, evaluate, understand, and apply statistics and data.

Questions to Consider in Searching for Data & Statistics


  • What are you looking to find out? (For example, availability of affordable and clean energy)

  • Are you looking for data about individuals, countries, states, institutions, etc? (For example, comparing between countries or comparing regions/states of the same country)

  • What characteristics are you interested in? (For example, household income levels, climate information, pollution information, etc)


  • What’s the date range you’re interested in?

  • How often is the information collected?

  • What is the periodicity for collection (annually, quarterly, etc)?


  • What geographic areas are you interested in?

  • If your first idea isn’t available, what are some other possibilities?


  • What organization (government agency or other) would have a need for this information?

  • What organization (government agency or other) would want to collect this information?

  • What is the organization’s interest in collecting the data?


  • Are you interested in all sorts of data or just specific types, like survey or longitudinal studies?

  • Will you be able to get access to the data you want? (Is it publicly and freely available?)

Source: Peter, K. & Kellam, L. (2011). Numeric data services and sources for the general reference librarian. Chandos Publishing.

Factors to Consider When Evaluating Statistics & Data


  • Who collected it?
  • Was it an individual or organization or agency? 
  • The data source and the reporter or citer are not always the same. For example, advocacy organizations often publish data that were produced by some other organization. When feasible, it is best to go to the original source (or at least know and evaluate the source).
  • If the data are repackaged, is there proper documentation to lead you to the primary source? Would it be useful to get more information from the primary source? Could there be anything missing from the secondary version?


  • How widely known or cited is the producer? Who else uses these data?
  • Is the measure or producer contested?
  • What are the credentials of the data producer?
  • If an individual, are they an expert on the subject?
  • If an individual, what organizations are they associated with? Could that association affect the work?

Objectivity & Purpose

  • Who sponsored the production of these data?
  • What was the purpose of the collection/study?
  • Who was the intended audience for or users of the data?
  • Was it collected as part of the mission of an organization? Or for advocacy? Or for business purposes? Other purposes?


  • When were the data collected? Keep in mind that there is often a time lag between collection and reporting because of the time required to analyze the data.
  • Are you looking for the most recent figures available? If so, are these the newest available figures? 

Collection Methods & Completeness

  • How are the data collected? Count, measurement or estimation?
  • Consider what data points/questions were collected/asked and left out. Even a reputable source and collection method can introduce bias.
  • If a survey, what was the total population -- how does that compare to the size of the population it is supposed to represent?
  • If a survey, what methods used to select the population included, how was the total population sampled?
  • If a survey, what was the response rate?
  • What populations are included? Excluded?

Consistency / Verification

  • Do other sources provide similar numbers?
  • Can the numbers be verified?

Source: Gould Library. (2020). Data, datasets, and statistical resources research guide. Carleton College.