Data and Advocacy
Consider the following when evaluating your data or statistics:
- Who collected it? Was it an individual, organization or agency?
- The data source and the publication/website where it appears 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? What organizations are they associated with? Could that association affect the work?
Objectivity & Purpose
- What was the purpose of the collection/study?
- Was it collected as part of the mission of an organization? Or for advocacy? Or for business purposes?
- Who sponsored the production of these data?
- Who was the intended audience for or users of the data?
- When were the data collected? There is often a time lag between collection and reporting because of the time required to analyze the data.
- Are these the newest figures? Sometimes the newest available figures are a few years old. That is okay, as long as you can verify that there isn't something newer.
Collection Methods & Completeness
- How are the data collected? Count, measurement or estimation?
- Even a reputable source and collection method can introduce bias. Crime data come from many sources, from victim reports to arrest records.
- If it was a survey:
- what was the total population -- how does that compare to the size of the population it is supposed to represent?
- what methods used to select the population included, how was the total population sampled?
- what was the response rate?
- What populations included? Excluded?
Consistency / Verification
- Do other sources provide similar numbers?
- Can the numbers be verified?
** (Adapted from Gould Library, Carlton University)
Become Data Literate in 3 Simple Steps, Nicholas Kayser-Bril, DataJournalism.com
3 Ways to Spot a Bad Statistic, Mona Chalabi, TED Talks
Statistical literacy:Thinking critically about statistics, Of Significance: A Topical Journal of the Association of Public Data Users
Using Data for Advocacy
Data Advocacy: Visualizations for Promoting Change (Just Publics@365, CUNY)
Data Visualization and Infographics: Using Data to Tell Your Story (TechImpact/Idealware)