Herb Weisberg


Milo Schield, Editor

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

Added StatLit.org webpage for Jerome Cornfield.

RSS: Call for Grant Ideas.  Submit by July 31, 2015.

The Improbability Principle: Why Coincidences, Miracles, and Rare Events Happen Every Day by David Hand. TOC:1 The Mystery; 2 A Capricious Universe; 3. What is Chance? 4 The Law of Inevitability; 5 The Law of Truly Large Numbers; 6 The Law of Selection; 7 The Law of the Probability Lever; 8 The Law of Near Enough; 9 The Human Mind; 10 Life, the Universe and Everything; 11 How to Use the Improbability Principle.

What is wrong with THE Introductory Statistics Course.  Schield USCOTS 2015.   Statistical Literacy roundtable

New classroom video:  Statisticians: Making our World a Better Place.  Schield 2015 USCOTS.  4.5 minutes

Statistical Literacy online course for teachers (no credit):  May 11-June 29. Syllabus, Textbook and Registration

April 29: Congratulations go to Tyler VanderWeele, winner of the 2015 ASA “Causality in Statistics Education Award” for his book “Explanation in Causal Inference” (Oxford, 2015). The award ceremony will take place at the 2015 JSM conference, August 8-13, in Seattle. Another good news, Google has joined Microsoft in sponsoring next year’s award, so please upgrade your 2016 nominations. For details of nominations and selection criteria, see www.amstat.org/education/causalityprize/.   Source: www.mii.ucla.edu/causality/?m=201504

Aug 4.   "Willful Ignorance" by Herb Weisberg (picture above) is now available!!  [Editor:  This book is my #1 pick for 2014.]   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 one!  Amazon US

Two Big Ideas for Teaching Big Data: Coincidence and Confounding by Milo Schield. ECOTS invited paper downloaded 4,200 times in the seven months it has been posted in 2014.   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]

2014 10: Highest Monthly Downloads: October had 45,000 downloads from this site: the highest number in our ten-year history. Last year's monthly  high was 26,000 in May.  The biggest cause is the download of the the PowerPoint demos to create various statistics and models using Excel: over 67,000 YTD.  The "Create-Lognormal-Excel2013" demo has had 36,000 downloads so far this year.

2014 11: Highest Monthly Index Views @ StatLit.org:  November had 6,200 index views -- 33% more than last year's monthly high.

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 2015. A $10,000 prize or two $5,000 prizes will awarded this year. For additional information about the award, see the 2012 announcement, the 2013 winner and the 2014 winner. Nominations and questions should be sent to the ASA office at educinfo@amstat.org. The nomination deadline is February 15, 2015. Visit 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 


Search StatLit Site

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

Search the web Search this site

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



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

2015 SLIDES and WORKSHEETS HOSTED (by month)

07  2013 MSMESB: MS Business Analytics program.  Nargundkar.    slides



12  AMSTAT: Causality in Statistics Education Award 2013. ASA News

12  Most stat analysis not done by statisticians Simply Statistics 2013

12  Simpson's Paradox in Psychological Science by Kievit et al. 2013.

12  Statistical Literacy Explained by Hewson, Teaching Statistics, 2013

12  Headlines in a Math-Literate World by Orlin, Huffington Post, 2013

12  RSS GetStats Statistical Literacy Campaign and Initiatives. 2014

12  SIGMAA-QL 2013 Newsletter.   Bennet: Writing for general public.

11  Call for Statistical Literacy papers. 2014 Stat-Ed Research Jrnl.

11  Relative Risk Cutoffs for Statistical Significance. Schield 2014

10  SRTL-9 Proposal: Informal Doorways to Modeling. Schield  2014

09  Limitations and Uses of Convenience Samples Kriska et al. ASA 2013

09  Seeing how Statistical Significance is Contextual.  Schield 2003.

08  Simpson's Paradox #30 Classic Problems in Probability. Gorroochurn

08  Simon Schild Maps: Bellenberg Germany & Benton County IA. 2014

08  Schild Family journey from Bellenberg Germany to America. 2002

07  2013 MSMESB/DSI Annual Report by Robert Andrews

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

04  Teaching Big Data at Georgetown. Sigman et al. Decision Line 2014

03  Augsburg TIDES Proposal: Summary AACU Schield 2014 Full proposal

02  Augsburg's NSF Proposal: Summary.  Schield 2014 Full

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

2014 SLIDES and WORKSHEETS HOSTED (by month)

11  Business Analytics and Data Science. Schield DSI 2014 slides

10  Statistical Literacy+Coincidence. Schield NNN1 Workshop 2014 slides
10  Explore Log-Normal Incomes Schield NNN2 2014 Slides xls  Update

10  Creating Distributions Empirically. M. Schield. NNN3 Workshop Slides

10  Statistically-Significant Correlations. Milo Schield. NNN4 2014 Slides

10  Segmented Linear Regression. Schield. NNN5 Workshop 2014 Slides

08  Top 30 Learning Goals for Introductory Sociology. Persell  2010  List

08  Social Science Reasoning & QL Learning Goals Caulfield+Persell'06List

07  2013 MSMESB: Predictive Analytics course. Levine et al.         slides

07  2013 MSMESB: Spreadsheet Analytics. James R. Evans.          slides

07  2013 MSMESB: Implications of Big Data for Stat Ed. Berenson  slides

07  2013 MSMESB: Big Data & Statistics Instruction. Berenson      slides

07  2013 MSMESB: Big Data in Stat 101: Small changes. McKenzie slides

07  2013 MSMESB: Create Business Analytics class. Kirk Karawan.  slides

07  2013 MSMESB: Getting Analytics into the curriculum. Karawan. slides

07  2013 MSMESB: Analytics and the Evolving Workforce. LaBarr.   slides

07  2013 MSMESB: MS Business Analytics program.  Nargundkar.    slides


Top 20 Downloads of Papers (or slides if no paper):
7,860 Percentage Graphs in USA Today Schield 2006 ASA. Total 100,052
7,043 Responsible Stats...to Shape Public Opinion by A Nelson 6up 2011
4,602 Two Big Ideas for Teaching Big Data Schield 2014 ECOTS [**May]
3,769 Framework for Interpreting Tables & Graphs  Kemp & Kissane 2010
3,172 Statistical Literacy in Adult College Students B. Wade 2009 Thesis
2,891 Quantitative Scholarship: From Literacy to Mastery U.Texas 2009
2,696 Statistical Literacy: A New Mission for Data Producers Schield '11
2,625 Interpreting the Cumulative Frequency Distribution Winkler 2009
2,613 Check Distributional Assumption: “Benford’s Law”  Goodman 2013
2,596 Likert & Visual Analog Scales Tom Knapp 2013
2,578 Presenting Confounding Graphically via Standardization Schield '06
Practical Approach to Intro Poli-Sci Statistics Course Klass 2004
2,173 To Pool or Not to Pool by Tom Knapp 2013
1,503 Statistical Literacy Guide.  Bolton, UK  2009
1,466 Teaching Statistical Literacy by Haack 1978, Teaching Statistics

1,289 Statistical Literacy Curriculum Design.  Schield, 2004 IASE Sweden
1,138 The Undetectable Difference: The “Problem” of p-Values. Goodman 
1,055 Developing a Test of Normality in the Classroom Jernigan 2012 ASA
1,054 Substantive significance of regression coefficients. Miller 2008 ASA
   991 Assessing Students’ Attitudes by Millar & Schau  2010 ASA.

Top Downloads of Excel-Related Slides (All by Schield)

1   37,203 Create lognormal in Excel 2013. 6up 1up Demo

2.    7,278 Model Logistic Regression using Excel 2013. 6up 1up

3.    6,117 Using the Z-test function in Excel 2008   6up 1up

4.    4,008 COUNTIF histograms: Excel 2013 6up 1up demo

5.    3,905 Confidence intervals with Excel 2010   Slides   Demo Output

6.    2,577 T-Test command with Excel 2013   6up 1up

7.    2,475 Trendline 2Y1X with different scales.   6up  1up

8.    1,900 Create Pivot Tables using Excel 2008  6up 1up

9.     1,563 Using the T-Test function in Excel 2008.   6up 1up

10       508 Regress 3 Factor using Linear Trendline Excel 2013  6up 1up

11       466 Create lognormal distribution Excel 2008. 6up 1up  Output

12       273 Model using Linear Trendline in Excel 2013. 6up 1up


















  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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IMS             UPCOMING PROFESSIONAL EVENTS             Statistics

  • 2015 Aug 9-13.  Joint Statistical Meeting in Seattle, WA.
    Sunday 8/09:
    3:05 #040 Looking Deeper into Student's Engagement, Learning Style, and Attitudes by Chauhan* & Zubovic (Purdue U. Fort Wayne)
    *  4:45 #067 Causal Inference in Environmental Science and Agriculture: Opportunities and Challenges by Molly Davies
    *  5:05 #065 Intro Stats in the 21st century by Richard De Veaux* (Williams)
    Monday 8/10:
    *  7:00 #095 Roundtable Writing in the Statistics Classroom by Kim Love-Myers* (Statistical Consulting Center, UGA)
    *  8:50 #143 Teaching Study Design Principles vs. Data Analysis by Tisha Hooks* and April Kerby (Winona State)
    *  9:05 #143 What Would Fisher Do? Promoting a Rich Understanding of Model Construction by Couton & Stroup (U. Nebraska - Lincoln)
    *  9:20 #143 Including a History of Statistics Course in your Curriculum by Phyllis Curtiss* and Kirk Anderson (Grand Valley State)
    * 10:35 #185 Teaching Meta-Analysis: Concepts, Controversies, and Resources by Deborah Dawson (Univ. Iowa)
    * 10:50 #185 3 Related Paradoxes by Harry James Norton, Carolinas Medical Center & George Divine, Henry Ford Hospital
    * 11:05 #185 From Measurement Errors to Normal Distributions: History and Pedagogical Implications by Ilhan Izmirli (GMU)
    * 11:05 #186 SBSIG Visual Analytics and the Introductory Statistics Course: Time for a Paradigm Shift by Benjamin Adams (U. AL)
    * 12:05 #182 Graphical causal models: the next multimodel inference regime change needed in Ecology? Irvine* and Gitelman (Oregon St)
    *  2:00 #240 Panel: GAISE in Increasingly Data-Centric World Rob Carver, John Gabrosek, Megan Mocko, Paul Velleman, Beverly Wood
    Tuesday 8/11:
    *  7:00 #276 Roundtable Resampling in the Undergraduate Curriculum by Tim Hesterberg (Google)
    * 10:30 #377 Poster #12: Estimating Causal Effects..in RCTs w. Provider-Subject Noncompliance by Elisa Sheng* & Xiao-Hua Zhou (U. Wa)
    * 10:35 #330 A new criterion for confounder selection by Tyler VanderWeele* (Harvard) and Ilya Shpitser (U. Southampton)
    * 11:50 #362 Graphical Framework for Causal Reasoning: Multivariate, Multilevel & Longitudinal Settings. Theobald & Richardson (U. Wa)
    * 11:20 #366 Reading Assignments for the Statistics Classroom by Scott Mcclintock* and Steve Soltys (Elizabethtown College)
    * 11:35 #366 Quantitative Writing: Communicating Data by Kimberly Massaro* and Gail Pizzola (UTSA)
    * 11:50 #366 Children statistical literacy: Empowering & informing future decision makers by Matilde Sanchez-Pena & J. Main (Purdue)
    * 12:05 #366 Statistical Literacy for Managers by Milo Schield (Augsburg)
    * 12:30 #389 Roundtable: Innovative Ways for Teaching Large Statistics Courses by Stacey Hancock (U. Calif. Irvine)
    *  2:00 #404 Invited Panel: Statistics Education via Online Courses. John McGready, James Rosenberger, Simon Sheather & Camille Fairbourn
    Wednesday 8/12:
    *  7:00 #456 Roundtable Quantitative Statistics Courses Are Very Qualitative by Leanna House* and Scotland Leman (Virginia Tech)
    *  8:55 #480 Unraveling Bias in Online [Natural] Experimentation by Chris Harland (Microsoft)
    *  9:15 #480 How Credible are Observational Estimates of Causal Effects from 'Big Data' by Eytan Bakshy* and Dean Eckles (Facebook)
    *  9:15 #487 Relationship b/t Verbal Reasoning Skills and Statistical Literacy... by Elizabeth Johnson*(GMU) & D. Keosayian (Wilkes)
    *  9:20 #487 what statistically significant relationship looks like [in scatter plots] by Aaron Fisher*, Anderson, Peng & Leek (John Hopkins)
    *  9:30 #487 Reinforcing Experimental Design with Activities by Paul Stephenson*, Curtiss, Richardson and Reischman (Grand Valley State)
    *  9:40 #487 Changing How Students Think About Statistics by Paul Plummer (U. Central Missouri)
    *  9:55 #487 Are Pie Charts Really So Bad? by Michael Posner* and Joseph Reiter (Villanova)
    * 10:05 #490 Causal inference for ordinal outcomes by Alexander Volfovsky*, Edo Airoldi and Donald Rubin (Harvard)
    * 10:50 #545..Evolution of Statistical Terms such as Analytics, Big Data, and Data Science by John McKenzie, Babson College
    * 11:00 #517 ...Delivering Impactful End-to-End Stories to Executive Audiences by Paul Swiontkowski (Microsoft)
    *  3:05 #597 On causal interpretations of race in regressions adjusting for confounding and mediating variables by Whitney Robinson (UNC)
    Thursday 8/13:
    *  9:05 #654 Peer Assessment in the Statistics Classroom by Dennis Sun (Stanford & Google)
    * 10:35 #691 Bias Amplification: The Case of Fixed-effects by Joel Middleton*, Marc Scott, Jennifer Hill and Ronli Diakow

  • 2016 July 24-31:  ICME13. Start planning for the 13th International Congress on Mathematical Education (ICME13), July 24-31, 2016, Hamburg Germany. (FYI, just before ICME13, IASE plans a Roundtable in Berlin

    Topic Study Groups: TSG14 (Teaching and learning of Probability), TSG15 (Teaching and learning of Statistics), TSG23 (Mathematical Literacy). Also look at TSG6 (Adult lifelong learning of mathematics) and TSG3 (Mathematics education in and for work). Deadline for submission of papers for TSGs = Oct 1, 2015



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

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