Herb Weisberg


Milo Schield, Editor

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

2016 July: Offering STAT 102: Social Statistics for Decision Makers. Schield IASE Roundtable in Berlin.

2016 Sept:  A Field Guide to Lies: Critical Thinking in the Information Age by Daniel Levitin. Table of Contents and Introduction

2016 March:  Seven Pillars of Statistical Wisdom by Stephen M. Stigler.  "What gives statistics its unity as a science? Stephen Stigler sets forth the seven foundational ideas of statistics―a scientific discipline related to but distinct from mathematics and computer science."   "I will not try to tell you what statistics is -- or is not. I will attempt to formulate seven principles, seven pillars that have supported our field in different ways in the past and promise to do so into the indefinite future."  TOC 1. Aggregation: From Tables and Means to Least Squares 2. Information: Its Measurement and Rate of Change 3. Likelihood: Calibration on a Probability Scale 4. Inter-comparison: Within-Sample Variation as a Standard 5. Regression: Multivariate Analysis, Bayesian Inference and Causal Inference 6. Design: Experimental Planning and the Role of Randomization 7. Residual: Scientific Logic, Model Comparison and Diagnostic Display. "The usefulness of [these] seven basic statistical ideas: 1. The value of targeted reduction or compression of data.   2. The diminishing value of an increased amount of data. 3. How to put probability measuring stick to what we do. 4. How to use internal variation in the data to help in that.  5. How asking questions from different perspectives can lead to revealingly different answers. 6. The essential role of the planning of observations. 7. How all these ideas can be used in exploring and comparing competing explanations in science.

2016 Feb: Quantitative Research Methods by T. R. Knapp

Introduction to Statistical Investigations by Tintle, Chance, Cobb, Rossman, Roy, Swanson & VanderStoep (2015).   Wiley Description & TOC  2014pb

The Math Myth and Other STEM Delusions Book by Andrew Hacker. The Wrong Way to Teach Math 2/2016. NY Times  Is Algebra Necessary? 7/2012 NY Times.  Reviews: Goldstein "Hecker: Down with Algebra II".   2012 Rebuttals: Mehta, Devlin.  2016 Rebuttals:  Devlin

2015 August:  Statistical Inference for ManagersMilo Schield. ASA JSM 6up 1up

2015 July:  Added StatLit.org webpage for Jerome Cornfield. 

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

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 


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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



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 (Months stats tabulated):
8,172 Responsible Stats...to Shape Public Opinion by Nelson 6up '11 (12)
3,348 Percentage Graphs in USA Today Schield 2006 Total 100,052  (12)
2,674 Two Big Ideas for Teaching Big Data Schield 2014 ECOTS         (9)

2,404 Practical Approach Intro Poli-Sci Statistics Course Klass 2004  (12)
2,231 Framework Interpreting Tables & Graphs  Kemp/Kissane 2010   (12)
2,196 Statistical Literacy Guide.  Bolton, UK  2009                         (11)
2,020 Likert & Visual Analog Scales Tom Knapp 2013                        (8)
1,518 Making Statistics Memorable: New Mnemonics Lesser 2011 JSM (9)

1,367 Presenting Confounding Graphically/Standardization Schield '06  (8)
1,336 Statistical Literacy Curriculum Design    Schield, 2004 IASE       (8)
1,063 Substantive significance of regression coef.  Miller 2008 ASA     (7)
  993 Statistical Literacy in Adult College Students Wade 2009 Thesis (4)
  894 Check Distributional Assumption: Benford’s Law  Goodman 2013  (5)
  869 Interpreting the Cumulative Frequency Distribution Winkler 2009 (6)
  700 Statistical Literacy: New Mission for Data Producers Schield '11 (3)
  653 Statistical Inference for Managers  Schield ASA 2015               (3)

Top Downloads of Excel-Related Slides (All by Schield)
1. 13,167 Create lognormal in Excel 2013. Slides

2.  5,717 Model using Linear Trendline 2Y1X Excel 2013.  Slides

3.  4,989 T-Test command with Excel 2013   Slides

4.  2,381 Create histograms using functions w Excel 2013 Slides

5.  1,930 Create Pivot Tables using Excel 2008  Slides

6.  1,889 Model using Linear Trendline Excel 2013  Slides

7.  1,468 Graph nominal data w Excel 2013 Slides  

8.  1,367 Using the Z-test via functions in Excel 2008  Slides

9.    952 Model Logistic Regression MLE using Excel 2013. Slides

10   802 Model Toolpak Regress linear 3 factor 1Y2X Excel 2013. Slides

11   762 Model Logistic Regression OLS1C Excel 2013  Slides


















  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             2016 PROFESSIONAL EVENTS             Statistics

  • 2016 Aug 3-8  MATH-FEST    Q/L PanelQ/L & Statistical Literacy by Schield: Slides  Audio

  • 2016 Aug 1-4 JSM   StatEd Sessions.  Schield's selection of StatEd papers.

    #129 Monday 8:30 - 10:20 Advancing Statistical Literacy — Contributed Papers
    * 8:35 Top 5 Reasons You Can't Blame. Students for Not Getting Inference — Chris Malone, Winona State U.
    * 8:50 Twelve Big Ideas for Introductory Statistics — Milo Schield, Augsburg College  Slides  Audio
              Augsburg Student Evaluations of STAT 102: Social Statistics for Decision Makers.
    * 9:05 Students' Ratings of the Utility of Key Concepts in Intro Statistics — Rossi A Hassad, Mercy College
    * 9:20 Effect size really does matter — Jeffrey Witmer, Oberlin College
    * 9:35 Emphasizing critical thinking in introductory statistics — Roger Woodard, North Carolina State University
    * 9:50 Students' Understanding of Expected Value — Hyung Kim ; Tim Fukawa-Connelly, Temple University
    *10:05 Importance of retention: Preparing students for workforce — Michael Posner & Meghan Buckley, Villanova U.

     * Type & Quality of Graphs Used in the ASA/NCTM Annual Poster Competition (2013-2016) by Symanzik, Robbins and Heiberger.
     *  Students’ performance and attitudes towards a flipped classroom for introductory statistics. Carl Lee, Central Michigan U., Mt. Pleasant, MI

    Incorporating Visual Literacy Standards in an Introductory Statistics Course. Jill Young, Claudia Ruediger. SE Missouri State Univ., Cape Girardeau, MO

    The Evaluation of a Pedagogical Tool for Quantitative Literacy by Gerald Iacullo,   Berkeley College, NY, NY

    Restructuring Introductory Statistics Courses to Free Class Time ... by Bonnie Moon, Craig Johnson and Ryan Cromar.  ASA  BYU-Idaho
    * P-Values and the Likelihood Principle by Andrew Neath, Southern Illinois University, Edwardsville, IL.
    * Do the Write Thing: Bolstering Student Comprehension in Introductory Statistics by Bernard Dillard, Fashion Institute of Technology, NY

  • 2016 July 24-31:  ICME13. Start planning for the 13th International Congress on Mathematical Education (ICME13), July 24-31, 2016, Hamburg Germany. (FYI, IASE plans a Roundtable in Berlin just before ICME13.) 
    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   TSG15 Presentations.     TSG23 Presentations

    IASE Presidential Session, IPS104 (Sat. July 30, 09:00 to 10:10) will feature two distinguished colleagues, Jim Ridgway (Durham, UK) and Joachim Engel (Ludwigsburg, Germany) who will jointly speak about: "Implications of a data-rich, multivariate world: New needs and directions in statistical education".

    Lunch Roundtable Discussion: "What do we do about the 'literacy' in statistical literacy, at the college level?" (LRTD-09; leader: Iddo Gal, Thurs. July 28, 12:30 to 14:00).

    Wed. July 27:
    *IPS021* - Statistical Literacy for Decision Makers, Room 207, Jul 27
    *IPS043* - Which is the right approach to learn statistics? Cues from different educational contexts, Room 202C, Jul 27,
    *IPS079* - Statistical Methods in Computerized Adaptive Testing, Room 201AB, Jul 27
    *IPS039* - Brazilian Statistical Association (ABE): Contributions to Education and Dissemination of Statistics in Brazil, Room 207, Jul 27
    *IPS138* - The LISA 2020 Program to Build Statistical Capacity and Research Infrastructure in Developing Countries, Room 201C, Jul 27
    *STS053* - Challenges and obstacles in improving statistical literacy, Room 204C, Jul 27
    *STS074* - Apps and e-learning resources for training in Official Statistics, Room 204A, Jul 27

    *IPS041* - Open Data, Civil Society and Monitoring Social Progress: Challenges for Statistics Education, Room 201C, Jul 28
    *STS056* - Big Data Analytics - experiences and perspective on education and talent training, Room 204B, Jul 29
    *IPS042* - Quantitative practices that might arise with the use of new technological capabilities for exploring data, Room 205, Jul 30
    *IPS076* - Multilevel modeling in evaluation and large-scale assessments, Room 210, Jul 31
    *IPS040* - Ethics in teaching and practicing statistics: Learning from real-life ethical dilemmas, Room 210, Jul 31

  • 2016 July 19-22: IASE Roundtable Conference (Invited).  HomeDetailed schedule. Held at the Max Planck Institute for Human Development (MPIB) in Berlin, Germany.  "About 40-50 folks from around the world and the host country will work together on a unique theme: “Promoting understanding of statistics about society“. The Roundtable aims to advance current knowledge about ways to improve the understanding of data and statistics related to key social phenomena." Program  Theme & papers   Submission Guidelines    About  Local  

    Schield proposal Abstract  Overview: 1 Social Statistics Slides Audio;   2 Confounding Slides Audio;    3 Inference Slides Audio   Survey   Schield paper (draft): Offering STAT 102: Social Statistics for Decision Makers

  • 2016 May 16-20:  ECOTS 16.  Access to sessions/papers.   Announcement.   Schield's classification of sessions and posters.
    Call for proposals #1 
    Submit by Feb 1. "Proposals should be related to the conference theme of "Changing with Technology". Advances in technology provide both new opportunities and new demands when it comes to statistics education. Technology is inspiring change in many different aspects of statistics education: what we teach (curriculum), how we teach (pedagogy), who we teach (audience), and why we teach (goals). Proposals can address technology-induced change in any of these areas. All proposals are due by February 1, 2016.   For more details about eCOTS 2016 and to submit a proposal, please visit www.causeweb.org/ecots/ecots16/. If you have any questions, please contact Kari Lock Morgan at klm47@psu.edu. Thanks!"


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

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