Herb Weisberg


Milo Schield, Editor

Authors Popular StatLit News Authors-Academic Statistical Literacy Numeracy Statistical Reasoning

Aug 4.   "Willful Ignorance" by Herb Weisberg (picture above) is now available!!  [Editor:  This book is my #1 pick for 2014 so far.]   Weisberg's grasp of statistical history is comprehensive without being over-whelming.  But this is more than just a history book on statistics.  Weisberg has a point to make -- that statisticians have mis-measured uncertainty!  And this mis-measurement involves "willful ignorance"!!!   These are fighting words for statisticians who consider the proper measurement of uncertainty to be their primary task.  For more details on Herbert Weisberg, visit his page.    If you buy one statistics book this year, buy this book!  Amazon US

Two Big Ideas for Teaching Big Data: Coincidence and Confounding by Milo Schield. ECOTS invited paper downloaded 2,200 times in the first 90 days after being posted.   See also Schield slides presented at Big Data panel.

"I hope that...statistical literacy will...rise to the top of your advocacy list"  Ruth Carver, ASA 2012 Presidential Address

29% of US Freshman took stats in high school (15% took AP Stats), so 14% took non-AP Stats. 2012 Am. Freshman

Spurious Correlations (More than 9,000 computer-generated as of 5/2014): For example: Number of people who died by becoming tangled in their bed sheets correlates with Total revenue generated by skiing facilities (US).  [Great examples, but a high correlation coefficient between two times series does not imply statistical significance -- much less a causal connection. See Cross-correlation.  Editor]

Highest Monthly Downloads:  StatLit.org website had more than 30,000 downloads per month in April, May and June: the highest number in our ten-year history. The biggest cause is the download of the the PowerPoint demos to create various statistics and models using Excel: almost 30,000 YTD.  The "Create-Lognormal-Excel2013" demo has had almost 17,000 downloads so far this year. As of July 9, this demo was Google ranked #1 for this search: Create Lognormal Excel.

Judea Pearl (above) sponsors ASA Causality in Statistical Education Award. The committee is pleased to announce that a gift from Microsoft Research will enable the prize to double in 2014. A $10,000 prize or two $5,000 prizes will awarded this year. For additional information about the award, see the Amstat News articles at http://magazine.amstat.org/blog/2012/11/01/pearl/ and http://magazine.amstat.org/blog/2013/08/01/causality-in-stat-edu/. Nominations and questions should be sent to the ASA office at educinfo@amstat.org. The nomination deadline is April 15, 2014. Visit http://www.amstat.org/education/causalityprize/ for nomination information.


"Statistical literacy is the ability to read and interpret summary statistics in the everyday media: in graphs, tables, statements, surveys and studies.   Statistical literacy is needed by data consumers – students in non-quantitative majors: majors with no quantitative requirement such as political science, history, English, primary education, communications, music, art and philosophy. About 40% of all US college students graduating in 2003 had non-quantitative majors."    By Milo Schield in "Assessing Statistical Literacy: Take CARE" Ch 11 in Assessment Methods in Statistical Education, pp. 133-152.  Wiley 2010  Schield excerpts

Short introduction to Statistical Literacy.  For more on confounding, see Standardizing.

UK Parliament Briefing paper on Statistical Literacy

Statistical literacy: "the ability to read and interpret statistics, and think critically about arguments that use statistics as evidence"  United Nations Development Dictionary (move slider to "s") [link broken/missing in 2012]

Statistical literacy: "understanding the basic language of statistics (e.g., knowing what statistical terms and symbols mean and being able to read statistical graphs), and understanding some fundamental ideas of statistics." GAISE College Report 


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2014, 13, 12, 11, 10, 09, 8, 7, 6, 5, 4,  03

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Yearly highlights of grants, new books, conference papers (ICOTS, ISI, JSM, JMM), and events involving statistical literacy. 


Newest StatLit.org web pages: 


If you read just one article, read Challenging the state of the art in post-introductory statistics by Tintle, Chance, Cobb, Rossman, Roy, Swanson and VanderStoep. 


"By introducing confounding as 'one of the two major themes in statistical analysis' this paper is arguably the most important paper in statistical education since 2002 when Howard Wainer publicized 'The BK-Plot: Making Simpsons' Paradox Clear to the Masses'.  The Wainer and Tintle papers mark a new beginning of statistics education for the 21st century."  Milo Schield, StatLit Editor



07  Odyssey: A Journey to Lifelong Statistical Literacy  Schield ICOTS 2014  slides
05  Two Big Ideas for Teaching Big Data Schield ECOTS 2014 

01  Visualization of Economic Indicators. Thompson+Wallace. ASA 2013.

01  Fusion & causal analysis in big marketing data.  Mandel ASA 2013

01  Check Distributional Assumption: Benford’s Law. Goodman  ASA 2013

01  Challenge Statistical Claims in Media, Martinez-Dawson ASA 2013


09  Statistics Education: Steadfast or Stubborn? Schield Audio 1up 6up

09  Know your variables: critical element of statistical analysis: J. Miller


09  Responsible Stats ... to Shape Public Opinion by A Nelson 6up 2012

09  Key Components of Numeracy Infusion Course ...  Wilder ASA 2013

08  ASA President's Message: Statistical Literacy ... by R. Carver 2012

07  Anne Hawkins Response to New Pedagogy... by D. Moore ISR, 1997

06  Statistical Literacy of OB-GYN Residents, Anderson et al, JGME 2013

05  Odysseys2Sense: A Startup Guide by Schield  6up  Audio text

05  Effects of Course on Statistical Literacy by Rose Martinez-Dawson
05  Causality, Change, Dichotimization, Likert  & Analog Scales: T Knapp

05  Bias, N versus (N-1) Re-visited, To pool or not to pool by Knapp


Top Paper Downloads (# downloads)
 567 Percentage Graphs in USA Today. Milo Schield 2006 ASA
 437 Framework for Interpreting Tables & Graphs  Kemp & Kissane 2010
 402 Two Big Ideas for Teaching Big Data. M.Schield 2014 ECOTS [New in May]
 330 Responsible Stats ... to Shape Public Opinion by A Nelson 6up 2011
 276 To Pool or Not to Pool by Tom Knapp 2013
 274 Likert & Visual Analog Scales Tom Knapp 2013
 255 Statistical Literacy in Adult College Students B. Wade 2009 Thesis
 222 Interpreting the Cumulative Frequency Distribution Winkler 2009
 205 Practical Approach to Intro Poli-Sci Statistics Course Klass 2004
 202 Check Distributional Assumption: “Benford’s Law”  W. Goodman 2013

 188 Statistical Literacy Guide.  Bolton, UK  2009
 164 Quantitative Scholarship Plan: From Literacy to Mastery U.Texas. 2009
 163 Random Sampling versus Representative Samples 
Schield, 1994 ASA
 162 Making Statistics Memorable: New Mnemonics and Motivations Lesser, 2011


Top Excel-Related Slide Downloads (# downloads)
5,392 Create-lognormal-excel2013-demo-6up.pdf
  649 Ztest-function-excel-2008-6up.pdf
  631 Model-Logistic-Regression-1Y1X-Excel2013-6up.pdf
  608 Create-confidence-intervals-Excel2010-6up.pdf
  442 Create-Histograms-Countif-Excel2013-6up.pdf


Top Paper Downloads (# downloads)
4,185 Percentage Graphs in USA Today Schield 2006 ASA
3,556 Responsible Stats ... to Shape Public Opinion by A Nelson 6up 2011
Quantitative Scholarship Plan: From Literacy to Mastery  U.Texas. 2009
1,924 Framework for Interpreting Tables & Graphs  Kemp & Kissane 2010
1,888 Check Distributional Assumption: “Benford’s Law”  W. Goodman 2013
1,755 Presenting Confounding Graphically Using Standardization Schield STATS 2006
1,640 Statistical Literacy: A New Mission for Data Producers Schield 2011
1,623 Likert & Visual Analog Scales Tom Knapp 2013
1,577 To Pool or Not to Pool by Tom Knapp 2013
1,498 Interpreting the Cumulative Frequency Distribution Winkler 2009
1,485 Statistical Literacy in Adult College Students B. Wade 2009 Thesis
1,254 Two Big Ideas for Teaching Big Data. Schield 2014 ECOTS [**New in May]
1,055 Developing a Test of Normality in the Classroom  Jernigan 2012 ASA
   978 Practical Approach to Intro Poli-Sci Statistics Course Klass 2004
   881 Statistical Literacy Guide.  Bolton, UK  2009

   714 Random Sampling versus Representative Samples  Schield, 1994 ASA
   547 Statistical Literacy Curriculum Design Schield 2004 IASE Roundtable, Sweden
   495 Assessing Statistical Literacy: Take CARE (Excerpts).  Schield 2010
   419 Substantive Significance of Multivariate Regression Coefficients. Miller ASA 2008
   342 Making Statistics Memorable: New Mnemonics and Motivations Lesser, 2011




Top Excel-Related Slide Downloads (# downloads)
16,775 Create-lognormal-excel2013-demo-6up.pdf
 3,431 Ztest-function-excel-2008-6up.pdf
 3,120 Create-confidence-intervals-Excel2010-6up.pdf
 1,889 Model-Logistic-Regression-1Y1X-Excel2013-6up.pdf
 1,694 TTEST-Command-Excel-2013-6up.pdf
 1,399 Create-Histograms-Countif-Excel2013-6up.pdf
 1,190 Ttest-function-Excel-2008-6up.pdf


















  1. Percentage Graphs in USA Today. Milo Schield 2006 ASA Proceedings. 

  2. Statistical Literacy: Uses & Abuses of Numbers by Andrew Nelson 6up 

  3. Presenting Confounding Graphically Using Standardization by Milo Schield. 2006 STATS magazine. 

  4. Statistical Literacy: A New Mission for Data Producers by Milo Schield.  2011 SJIAOS

  5. Univ. Texas San Antonio: Quantitative Scholarship - Final Draft    Press release 2009

  6. Statistics for Political Science Majors. Gary Klass 2004 ASA


  • Victor Cohn (1989), News and Numbers

  • Darrell Huff (1954), How To Lie with Statistics

  • Edward Tufte (1995), Visual Explanations




S/L Books

Q/L Books


Q/L Texts



W. M. Keck Statistical Literacy Project

Web-accessible articles presenting a general background or overview.

Statistical Literacy:


Quantitative Literacy:

Thirteen articles involving the W. M. Keck Statistical Literacy Project:


  •  Making Sense of Statistics by Nigel Hawkes and Leonor Sierra. Section 1: If a statistic is the answer, what was the question?  Section 2: Common pitfalls.  Section 3: How sure are we?  Section 4: Percentages and risk; knowing the absolute and relative changes.  


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  • 2015 May 21:  Two Big Ideas for Teaching Big Data: Coincidence and Confounding by Milo Schield. ECOTS invited paper.  This paper was downloaded over 850 times in the first 10 days after being posted.   See also Schield slides presented at Big Data panel.

  • 2015 April.  DSJIE (Decision Science Journal of Innovative Education) is soliciting submissions for two special issues.  Rethinking Undergraduate Business Education: In the Classroom and Beyond (Call: submission deadline June 1, 2014).  Educational Innovation and Reform in the Decision Sciences Using Multidisciplinary and Collaborative Practices (Call: submission deadline August 1, 2014). 

  • 2015 April. Willful Ignorance: The Mismeasure of Uncertainty by Herbert Weisberg.  To be available in July from Amazon.

  • 2014 Feb 28. Improving [NZ] journalists’ statistical literacy via a new unit standard

  • 2014 Feb 16.  Misconceptions of science and religion found in new study   • Nearly 60 percent of evangelical Protestants and 38 percent of all surveyed believe “scientists should be open to considering miracles in their theories or explanations.” • 27 percent of Americans feel that science and religion are in conflict. • Of those who feel science and religion are in conflict, 52 percent sided with religion. • 48 percent of evangelicals believe that science and religion can work in collaboration. • 22 percent of scientists think most religious people are hostile to science. •Nearly 20 percent of the general population think religious people are hostile to science. • Nearly 22 percent of the general population think scientists are hostile to religion. • Nearly 36 percent of scientists have no doubt about God’s existence.

  • 2014 Jan Teaching Big Data: Experiences, Lessons Learned, and Future Directions by by Betsy Page Sigman, William Garr, Robert Pongsajapan, Marie Selvanadin, Kristin Bolling, Greg Marsh, Georgetown University.  DSI p 9-15.

  • 2014: Jan 31. Texas drops Algebra II requirement; offers statistics and algebraic reasoning as alternatives.   The Texas Board of Education adopted two new math courses on Thursday that are designed to cover much of the same material offered in algebra II, which will no longer be required for high school students under the Legislature's academic curriculum overhaul.  The board voted ... to create two high-level math courses that could be alternatives: statistics and algebraic reasoning. Both will be developed by local schools under the guidance of the Texas Education Agency, and are designed to cover many of the same concepts covered in algebra II.

  • 2014: Jan 27 issue,  Woman's World magazine cover: "Breakthrough new study: This lifesaving diet lowers yours obesity risk 300%."   Page 19: "A new study found folks who eat vegan are 300% less likely to ever become obese.  That's triple protection against obesity for life!"  

IMS             UPCOMING PROFESSIONAL EVENTS             Statistics

  • 2014: Aug 2-7ASA-JSM 2014 Boston, MA.  
    Data Analytics in Business and Education. Topic-contributed panel. Sponsor: Section on Statistical Education.  Session 210126; Abstract 311733. Organizer: Milo Schield.  Chair: Robert Carver. Abstract: Data analytics is a rapidly changing field and a driving force in business, in schools of business and in statistics education. Panelists will provide background on their connection with data analytics in business and address three questions: (1) What statistical problems are you dealing with in analyzing data? (2) What statistical tools or techniques are you using or planning to use? (3) What underlying statistical ideas should statistical educators be teaching budding data analysts to help them better analyze "big data"?
    Monday 7:00 - 8:15 Roundtable:
    Teaching Introductory Statistics from a Bayesian Perspective by Jim Albert, Bowling Green State University.  There are challenges in teaching frequentist inference in the introductory statistics class and advantages to using a Bayesian viewpoint. Given the current popularity in the application of Bayesian methods, is it time to revisit the Bayes introduction statistics class?

    Monday 8:55 High-Dimensional Confounder Reduction for the Estimation of a Causal Quantity Mireille Schnitzer
    Monday 10:35 Causal Inference in the Presence of Interference and Unmeasured Confounders Cheng Zheng, University of Washington
    Monday 10:50 Toward a General Theory of Observational Causal Inference Sterling Portwood, Center for Interdisciplinary Science
    Monday 10:30: Quantitative Literacy and Introductory Statistics session.

    10:35 AM Connecting the Dots: Ways to Enhance a Noncalculus-Based Introductory Statistics Course — Adrienne Chu
    10:50 AM Introducing Hypothesis Testing with a Reflection Exercise and Student-Selected Synonyms — Frank Matejcikand Ahmed Al-Asfour
    11:05 AM Information Bias in Surveys — William Rybolt, Babson College ; George Recck, Babson College
    11:20 AM Teaching Statistics Using Political Polls — T. Ceesay, Merck
    11:35 AM Statistics in Journalism: Guiding Students to Uncrunch the Numbers — Nancy Pfenning, University of Pittsburgh
    11:50 AM Against All Odds: Inside Statistics — Marsha Davis, Eastern Connecticut State University
    12:05 PM Quantitative Literacy: Analysis of a Q-Course — Massaro, Orta, Boppana, Sass, Straud and Sanchez, Univ. of Texas at San Antonio

    Monday 2:05 PM The ASA Statistical Education Section: An Updated History with Emphasis on Its Last 25 Years — Halvorsen and McKenzie Jr.
    Monday 2:50 PM Introductory Statistics in Two-Year Colleges: Important to Our Future — Brian Kotz, Montgomery College
    Monday 3:20 PM Redesigning Business Statistics ... in Light of Common Core State Standards — Bodapati Gandhi and Srinivas P. Gandhi.
    Tuesday 7:00 Roundtable: Causal Inference in Statistics and Epidemiology James Robins, Harvard School of Public Health
    Tuesday 11:20 AM Analyzing Real Data Demands Database Skills — Robert Carver, Stonehill College
    Wed 8:30 Data Analytics in Business & Education. Victor Lo, Fidelity Dan Coyle, ProQuest Dan Katz, RepEquity Shaju Puthessery, DentaQuest
    Wed 10:30 Posters.
    30: Heuristic Biases in an Introductory Statistics Course — Andrew Neath, SIU Edwardsville
    31: At What Point Do Students' Attitudes Change? — April Kerby, Winona State University ; Jacqueline Wroughton, Northern Kentucky Univ.
    34: Teaching Hypotheses-Testing with Binomial Test and Pepsi-Coke Challenge — Phyllis Curtiss, John Gabrosek, Kirk Anderson, Grand Valley
    37: Discrepancies Between the Bivariate Correlation and Effect-Size Indices — Ariel Aloe, Univ. Northern Iowa ; Betsy Becker, Florida State
    44: From Measurement Errors to Normal Distributions: A Brief History and Its Pedagogical Implications — Ilhan M. Izmirli, George Mason U.
    46: Evolving a Traditional Business Statistics Course into a General Education Requirement Course — Cathy Poliak, U of Wisconsin-Milwaukee
    Wed 12:30 Roundtables:
    WL17: Visualization: Another V Associated with Big Data — John D. McKenzie Jr., Babson College
    WL18: Ideas for Teaching Statistics from Popular Science Books — Allan Rossman, Cal Poly, San Luis Obispo
    .......  Are Observational Studies Any Good? David Madigan, Columbia University 

    Thurs 8:30 Building Programs in Business Analytics Panelists: Alan Montgomery, Carnegie Mellon David Levine, Baruch College Harry Chernoff, New York University J. Keith Ord, Georgetown University Kellie Keeling, University of Denver

  • 2014 Oct 30-31.  NCTM Regional Conference Indianapolis, IN.  DATA & STATISTICS.
    Thursday, October 30, 2014
    8:00-9:00. How We are Lied to, Cheated and Manipulated by Statistics by Ed D Zaccaro Grades: 6 to 8, 9 to 12
    8:00-9:15. The Common Core Statistics-Plus/minus 4% by Gail Burrill. Grades 9 to 12.
    9:30-10:30 Ruling Out Chance by Roxy Peck. Grades 9 to 12
    2:00-3:00. Standard(s) Statistics: Engaging with CCSS Mathematical Practices and Statistical Content by Susan A. Peters Grades 6 to 8
    3:30-4:30. Statistics of Illumination by Allan J. Rossman. Grades 9 to 12.
    Friday, October 31, 2014
    12:30-1:30. k-12 Statistics Education from NCTM 1989 to Common Core 2013 by Jerry L. Moreno. General Interest/All Audiences
    1:30-2:45. Big Ideas in Grade 6-8 Statistics in the Common Core by J. Michael Shaughnessy. Grades 6 to 8
    2:00-3:00. LOCUS, A Tool For Assessing Statistical Reasoning in the CCSS by Douglas Whitaker and Tim Jacobbe. Grades 6 to 8, 9 to 12

  • 2014: Nov 22-25.  DSI Annual Meeting Tampa, FL.   Submission Deadlines.  May 1, 2014 - Full Paper Submissions and All Competition Entry Submissions.   May 15, 2014 - Abstract Submissions, Panel, and Workshop Proposals. 

  • 2014 Dec 5.  TAS Special Issue: "Statistics and the Undergraduate Curriculum".  Submitted papers should focus on aspects of statistical education beyond the first course for undergraduate (post-secondary) students...   Manuscripts should be submitted via the TAS website using the on-line portal system (see http://mc.manuscriptcentral.com/amstat). Authors should indicate in their cover letter that the paper is being submitted for the Special Issue on Undergraduate Programs (select the "Statistics and the Undergraduate Curriculum" manuscript type). All submissions are due by December 5th, 2014. Submitted papers will follow standard TAS external review procedures. The Special Issue will be published in November 2015. Inquiries and questions can be directed to any of the issue co-editors (nhorton@amherst.edu or Jo.Hardin@pomona.edu).

  • 2015: Jan 10-13. 2015 Joint Mathematics Meetings.  San Antonio, TX. Deadlines. Abstracts for All Speakers. 
    Selected contributed paper themes:
    *  Best Practices for Teaching the Introductory Statistics Course
    organized by Randall Pruim, Scott Alberts and Patti Frazer Lock.
    *  Statistics Education beyond the Introductory Statistics Course organized by Randall Pruim, Scott Alberts and Patti Frazer Lock.  
    *  Infusing QL into Mathematics and Nonmathematics Courses
    organized by Andrew Miller, Aaron Montgomery and Gary Franchy.
    Abstract submissions.   Details


QL = Q/L = Quantitative Literacy,   QR = Q/R = Quantitative Reasoning,    S/L = SL = Statistical Literacy,     S/R = SR = Statistical Reasoning

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