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(Dis) trusting Statistics: A Mini-Guide 1. What is the source of the statistics? What person or organization is providing this information? What are its qualifications and area of expertise? What are likely to be its biases, if any? How readily can you check the source – and possibly its sources in turn – for their qualifications, reputation, and consistency with other statistics offered by respected organizations and journals? 2. What is actually being claimed? Are words and terms clear, and used in a way consistent with definitions in the relevant field? Is the knowledge claim a factual one about the present or past, or is it a hypothetical prediction about the future? Does it report on a single study or a meta-study? If it reports a survey, how large and representative is the sample population? (Become familiar with the following: different kinds of averages; difference between correlation and causation; the terms “statistically significant”, "p-value", “p-hacking”, “background noise”.) 3. How are the statistics framed in context? Are the statistics used as supporting evidence for a knowledge claim or argument? (And how valid is that argument?) Are the numbers being used – instead or as well – to impress in a more emotional way? Do accompanying images or language clarify the significance of the statistics – and/or possibly heighten an emotional impact? Does it seem that other important statistical information has been omitted? 4. What is your own emotional response to the statistics? Do you notice in your own reaction to the statistics any inclination to accept or reject the statistics even before you’ve examined them as above? Do you detect in yourself any signs of confirmation bias – the inclination to believe whatever harmonizes with what you already think, or what you wish were true, regardless of the quality of the information? Eieen Dombrowski, Theory of Knowledge blog OUP https://educationblog.oup.com/category/theory-of-knowledge and Activating TOK https://activatingtok.net/ Cartoons by Theo Dombrowski, permission for use in ToK classrooms Vampires don't like sunshine. Can you tell?
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Page 1: (Dis) trusting Statistics: A Mini-Guide3hzqtk1fl9rx1oeesj3uzf0y-wpengine.netdna-ssl.com/wp... · 2019. 9. 30. · (Dis) trusting Statistics: A Mini-Guide 1. What is the source of

(Dis) trusting Statistics: A Mini-Guide

1. What is the source of the statistics?

What person or organization is providing this information?What are its qualifications and area of expertise? What arelikely to be its biases, if any? How readily can you checkthe source – and possibly its sources in turn – for theirqualifications, reputation, and consistency with otherstatistics offered by respected organizations and journals?

2. What is actually being claimed?

Are words and terms clear, and used in a way consistentwith definitions in the relevant field? Is the knowledgeclaim a factual one about the present or past, or is it ahypothetical prediction about the future? Does it report ona single study or a meta-study? If it reports a survey, howlarge and representative is the sample population?(Become familiar with the following: different kinds ofaverages; difference between correlation and causation;the terms “statistically significant”, "p-value", “p-hacking”,“background noise”.)

3. How are the statistics framed in context?

Are the statistics used as supporting evidence for aknowledge claim or argument? (And how valid is thatargument?) Are the numbers being used – instead oras well – to impress in a more emotional way? Doaccompanying images or language clarify thesignificance of the statistics – and/or possiblyheighten an emotional impact? Does it seem thatother important statistical information has beenomitted?

4. What is your own emotional response tothe statistics?Do you notice in your own reaction to the statisticsany inclination to accept or reject the statistics evenbefore you’ve examined them as above? Do youdetect in yourself any signs of confirmation bias – theinclination to believe whatever harmonizes with whatyou already think, or what you wish were true,regardless of the quality of the information?

Eieen Dombrowski, Theory of Knowledge blog OUP https://educationblog.oup.com/category/theory-of-knowledge and Activating TOKhttps://activatingtok.net/ Cartoons by Theo Dombrowski, permission for use in ToK classrooms

Vampires don't like sunshine. Can you tell?

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