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This guide is to help students and faculty with finding, sharing, and using data.

from D. Huff's famous book "How to Lie with Statistics", 1954

Misleading with statistics is called ‘statisticulation’. 

What was true in 1954 is just as true today.

According to Huff, here are seven common tactics used to knead statistical data into “dough.”

  • Biased sampling: polling a non-representative group.
  • Small sample sizes
  • Poorly-chosen averages: values across non-uniform populations.
  • Results falling within the standard error:  a survey can only be as accurate as its standard error.
  • Using graphs to create an impression:  accuracy and scale
  • “The semi-attached figure” stating one thing as a proof for something else
  • “Post-hoc fallacy”: incorrectly asserting that there is a direct correlation between two findings

source: Lavenda, D. (2012, March 2). 7 ways to lie with statistics and get away with it. Fast Company.

Additional e-books

Herzog, M., Francis, G., & Clarke, A. (2019). Understanding Statistics and Experimental Design: How to Not Lie with Statistics (1st ed. 2019. ed., Learning Materials in Biosciences). Springer.

Robinson, M., & Scherlen, R. (2014). Lies, damned lies, and drug war statistics: A critical analysis of claims made by the Office of National Drug Control Policy (Second ed.). State University of New York Press.

Recommended e-books available on JSTOR

Best, J. (2004). More Damned Lies and Statistics: How Numbers Confuse Public Issues. University of California Press.  

Best, J. (2012). Damned Lies and Statistics: Untangling Numbers from the Media, Politicians, and Activists. University of California Press. 

Best, J. (2013). Stat-Spotting: A Field Guide to Identifying Dubious Data. University of California Press. 

Zuberi, T. (2001). Thicker than Blood: How Racial Statistics Lie. University of Minnesota Press. 

Recommended Journal Articles

Monmonier, M. (2005). Lying with Maps. Statistical Science (20)3, 215-22. 

Moulton, E. (2013). Myth and reality: Interpreting the dynamics of crime trends: Lies, damn lies and (criminal) statistics. Police Practice and Research, 14(3), 219-227.

Rostami, Amir & Mondani, Hernan. (2015). The complexity of crime network data: A case study of its consequences for crime control and the study of networks. PloS One, 10(3), E0119309.

Steele, J. (2005). Darrell Huff and Fifty Years of "How to Lie with Statistics". Statistical Science, 20(3), 205-209.  

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