2014 2014            10/25/22

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Milo Schield, Editor

Website Highlights: 12th Year 2014
  • StatLit.org still growing:  2014: Downloads up 36%; Visits up 26%; Page views up 10%; Index views unchanged.  Over 360,000 downloads, 260,000 visits, 170,000 page views (50,000 home views).

  • 1 new page: Judea Pearl

  • Google ranked StatLit.org #8 for "statistical literacy" (Wikipedia is #1) . StatLit is the #1 website dedicated exclusively to statistical literacy.

  • ITD records:  StatLit.org has had more than a 1.7 million downloads, 1.4 million visits and 930,000 page views since 2005. 

Editor: Best New Trade/Professional Books in 2014


Editor: Top Papers/Journal Articles in 2014.


Top 10 Downloaded Articles from StatLit.org in 2014


  1. Percentage Graphs in USA Today. Milo Schield 2006 ASA Proceedings.  (7860; 7771; 17819; 19114; 11179; 13253; 14247; 8809) Total: 100,052

  2. Statistical Literacy: Uses & Abuses of Numbers by Andrew Nelson 6up  (7043; 4912)   Total: 11,955

  3. Two Big Ideas for Teaching Big Data. Milo Schield 2014 ECOTS 4602** New in May 2014.

  4. Framework for Interpreting Tables & Graphs  Kemp & Kissane 2010   (3769; 2805).

  5. Statistical literacy in adult college students: Table of Contents by Barbara Wade 2009 PhD Thesis.  (3172*; 672 [4]). 

  6. Univ. Texas San Antonio: Quantitative Scholarship - Final Draft    Press release 2009  (2891[5]; 1896 [4]).

  7. Statistical Literacy: A New Mission for Data Producers by Schield.  2011 SJIAOS (2696*; 3104[8]; 2815[10]; 1723).  Total: 10,338

  8. Interpreting the Cumulative Frequency Distribution of Socio-Economic Data. Othmar Winkler   2009 ASA (2625; 1515 [11]; 822[7])

  9. Reality Checks for a Distributional Assumption: The Case of “Benford’s Law” by William Goodman. (2613 [10])

  10. Assessing Validity and Reliability of Likert and Visual Analog(-ue) Scales by Thomas R. Knapp, 2013. (2596 [11]; 499 [4]).

Top 20 Downloaded Articles from StatLit.org in 2014
  1. Presenting Confounding Graphically Using Standardization by Milo Schield. 2006 STATS magazine. (2578[9]; 3709 [11]; 4646; 1289; 2084; 1985; 1616). Total: 17,907.

  2. Statistics for Political Science Majors. Gary Klass 2004 ASA (2423[11]; 1817; 1416[10]; 1389[10]; 596[6]; 765; 215)  Total: 8,621.

  3. To pool or not to pool Knapp 2013.  (2173[7])

  4. Statistical Literacy Guide by Bolton (UK) 2009.  (1503[9])

  5. Teaching Statistical Literacy by Haack 1978 in Teaching Statistics.  (1466 [2])

  6. Statistical Literacy Curriculum Design  by Milo Schield, 2004 IASE Roundtable, Sweden.  (1289[7], 760, 457).

  7. The Undetectable Difference: An Experimental Look at the “Problem” of p-Values by Bill Goodman 2010.  (1138[2]).

  8. Developing a Test of Normality in the Classroom by Robert Jernigan 2012. JSM ASA  (1055[2]).

  9. Interpreting the substantive significance of multivariate regression coefficients. Jane Miller 2008 ASA (1054[5]; 1630 [9]; 3118; 1625[11]; 2094; 1412).  Total: 10,933.

  10. Assessing Students’ Attitudes: The Good, the Bad, and the Ugly by Anne Millar and Candace Schau  2010 ASA. (991[4]; 1024 [6])


Total downloads: 368,000 in 2014; 265,000 in 2013; 246,000 in 2012; 198,000 in 2011; 207,000 in 2010; 184,000 in 2009; 106,000 in 2008. 
As of Dec. 2014, t
he StatLit website hosted 1,114 pdfs: 787 papers and 327 slides.


Numeracy: E-Journal

Numeracy is an open-access, peer-reviewed journal launched in 2008.  Numeracy aims to support education at all levels that integrates quantitative skills across disciplines. The journal seeks evidence-based articles. See Vacher's NECQL and PKAL presentations.

Numeracy Editors

Len Vacher (left) and Dorothy Wallace (right) are editors of Numeracy: Advancing Education in Quantitative Literacy published by the National Numeracy Network, supported by U. of S. Florida Libraries and hosted by the Berkeley Electronic Press™.

2014: Volume 7, Issue 1



Book Reviews:

2014 Volume 7, Issue 2




Book Review:

GRANTS FOR QR, QL, SR, ST and SL in 2014

Pearl: Causality in StatEd Prize

Judea Pearl, winner of the ACM 2011 Turing award, funded the ASA Causality in Statistics Education Prize for three years. Criteria: "does the most to enhance the teaching and learning of causal inference in statistics."  (1) equips students with skills needed for effective causal reasoning, and (2)  assists statistics instructors in gaining an understanding of the basics of causal inference ..."

Peterson+Balzer: Causality Prize

The ASA awarded the second Causality in Statistical Education prize to  Maya Petersen (right) and Laura B. Balzer for developing the path-blazing course “Introduction to Causal Inference” at the University of California at Berkeley: PH252D. This is a graduate course in their Master's degree program.  Course design and materials are available.   There were four nominations.

NSF Awards: 2007-2012

NSF awards mentioning these phrases by start-year (2012, 11, 10, 9, 8, 7): numeracy (3,1,2,3,6,1), quantitative reasoning (7,4,5,3,4,4), quantitative literacy (6,1,3,5,6,2), statistical thinking (2,3,4,2,0,1), statistical reasoning (1,1,2,0,0,0) and stat literacy (1,0,0,0,0,0). NSF database: QR (108), QL (55), numeracy (36), ST (33), SR (29), SL (13)??

Use "Advanced Search" Search on probabilistic (2,851), literacy (2,427), causal (1,580), confound (339),  "observational studies" (311), "observational study" (198), "quantitative reasoning" (115), "statistical significance" (84), "probabilistic reasoning" (71), "statistics education" (69), "quantitative literacy" (56), numeracy (40), "statistical thinking" (39),  "statistical education (38), "statistical reasoning" (32), "statistical literacy" (13), "probabilistic thinking" (3),  Over 3,000: statistical, education, learning, course, class,


Willful Ignorance

Willful Ignorance: The Mismeasure of Uncertainty by Herb Weisberg exposes the fallacy of regarding probability as the full measure of our uncertainty. The book explains how statistical methodology, though enormously productive and influential over the past century, is approaching a crisis. The author outlines a path toward the re-engineering of data analysis....

How Martians Discovered Algebra

This exploration of induction and philosophy of mathematics looks “under the hood” at the process of mathematical theorizing, a detailed view of how the process of induction actually works. It provides an alternative to ... modern logic, mathematics, and set theory ..., [Read this Ebook!  It  opens new pathways between math and philosophy! Ed.]

Statistical Thinking & Healthcare

Medical Illuminations: Using Evidence, Visualization and Statistical Thinking to Improve Healthcare by Howard Wainer.  "Medical Illuminations presents 13 contemporary medical topics (cf. mammograms, hip replacements, cancer maps). In each case it illustrates how modern tools of statistical thinking and statistical graphics can illuminate our understanding."  $28 192 p [Jan 4, 2014]

Mastering 'Metrics

Mastering 'Metrics: The Path from Cause to Effect by Joshua Angrist and Jörn-Steffen Pischke.  Presents the "five most valuable econometric methods, or what the authors call the Furious Five--random assignment, regression, instrumental variables, regression discontinuity designs, and differences in differences." 
$28 304 p [Dec 21, 2014]

Presenting Data

Presenting Data: How to Communicate your Message Effectively by Swires-Hennessey.  "He advocates following four key C words in all messages: Clear, Concise, Correct and Consistent. Following the principles in the book will lead to clearer, simpler and easier to understand messages which can then be assimilated faster. Anyone ... will benefit from reading this book. More importantly, it will also benefit the recipients of the presented data."



Predictive Business Analytics

Predictive Business Analytics: Forward Looking Capabilities to Improve Business Performance (Hc $35, 2014) by Lawrence Maisel and Gary Cokins.  Maisel and Cokins shatter the myths about this new paradigm, revealing how you can integrate predictive business analytics with other important business management & improvement methods, such as budgeting, forecasting & performance reporting.

Data Analysis; Business Modelin

Microsoft Excel 2013 Data Analysis and Business Modeling Paperback (pb $35, 2014) by Wayne Winston.  this hands-on, scenario-focused guide shows you how to use the latest Excel tools to integrate data from multiple tables—and how to effectively build a relational data source inside an Excel workbook.

Predictive Analytics 4 Dummies

Predictive Analytics for Dummies by Bari and Chaouchi ($23, 2014).  Covers predictive analytics basics, using structured and unstructured data, data mining, and algorithms and techniques for analyzing data.   Covers clustering, association, and statistical models; creating a predictive analytics roadmap; and applying predictions to the web, marketing, finance, etc,

S/S Models & Decision Analysis

Spreadsheet Modeling and Decision Analysis: A Practical Introduction to Business Analytics (hc, $135, 2014) by Cliff Ragsdale. 

Google Analytics Demystified

Google Analytics Demystified: A Hands-On Approach (pb, $36, 2014) by Joel Davis. The book's approach is unique.  Beyond detailed explanations of key concepts, the book provides you with a free website. You will be an active participant. You not only read what Google Analytics can do, but you can apply and explore key concepts on a working website without risk to existing data.

Big Data at Work

Big Data at Work: Dispelling the Myths, Uncovering the Opportunities (hc, $22, 2014) by Thomas H. Davenport.  Explains what big data means—and why everyone in business needs to know about it. Covers all the bases: what big data means from a technical, consumer, and management perspective; what its opportunities and costs are; where it can have real business impact...


Visualization Analysis & Design

Visualization Analysis and Design (pb, $75, 2014) by Tamara Munzner.  The book breaks down visualization design according to three questions: what data users need to see, why users need to carry out their tasks, and how the visual representations proposed can be constructed and manipulated. It walks readers through the use of space and color to visually encode data ...

Essentials of Business Analytics

Essentials of Business Analytics (hc, $195, 2014) by Camm & Cochran. Covers "the full range of analytics-descriptive, predictive, prescriptive--not covered by any other book. Includes step-by-step instructions to help students ... use Excel and powerful but easy to use Excel add-ons such as XL Miner for data mining & Analytic Solver Platform for optimization & simulation.

StatLit website: New Papers Hosted in 2014


12  Majority statistical analysis not performed by statisticians 2013 Simply Stats

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

12  Statistical Literacy Explained Paul Hewson Teaching Statistics, Feb 1. 2013

12  Headlines in Math-Literate World Ben Orlin Huffington Post,  Dec 4, 2013 blog

12  RSS GetStats Statistical Literacy Campaign and Initiatives. 2014

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

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

12  Big Data & Big Business: Should Statisticians Join?  Walker & Fung 2013 Signif.

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

12  Bayes: Why Bother by Thomas Louis, Johns Hopkins Bloomberg SPH. Slides

12  Single World Intervention Graphs (SWIGS) Robbins & Richardson. 2013. Slides

11  Causal Impact: Estimating Causal Effects in Time Series. Google 11/2014

11  SERJ: Call for papers on Statistical Literacy. 2014

08  Simpson's Paradox (#30) in Classic Problems in Probability by P. Gorroochurn

08  Top 30 Learning Goals for Introductory Sociology. Caroline Persell 1-Page List

08  Social Science & QL Learning Goals by Caulfield & Persell 2006  One-Page List

07  Odyssey: A Journey to Lifelong Statistical Literacy  Schield ICOTS 2014  Slides

05  Two Big Ideas for Teaching Big Data  Schield 2014 ECOTS.  Slides  Panel slides

04  Teaching Big Data by Sigman, DSI Magazine

01  Dynamic Visualization of Economic Indicators Thompson & Wallace. ASA 2013.

01  Fusion and causal analysis in big marketing data sets  Igor Mandel  ASA 2013

01  Reality Checks for Distributional Assumption: Benford Law Goodman  ASA 2013

01  Challenging Statistical Claims in the Media, Martinez-Dawson ASA 2013

Making Statistics More Effective in Schools of Business 2014

Decision Sciences Meeting

Making Statistics More Effective in Schools of Business (MSMESB) fielded over a dozen sessions at the 2014 annual meeting of the Decision Sciences Institute (DSI). Robert Andrews (Virginia Commonwealth University) was the key organizer, the chair of several sessions and the MSMESB webmaster.  2013 MSMESB DSI SIG Report.   Local copy  Keith Ord: What is AP Statistics?  Slides

Business Analytics:
John McKenzie (right): Introducing Big Data in Stat101 with small changes. Slides
Kirk Karwan: Creating Analytics Class at Furman.  Slides
Kirk Karwan: Analytics Curriculum.  Slides
Satish Nargundkar: Georgia State Analytics.  Slides
James R Evans:  Spreadsheet Analytics.  Slides
Robert Stine: Big Data Implications for intro stats.  Slides

Levine, Szabat and Stephan

David M. Levine (Baruch College: CUNY), Kathryn Szabat (LaSalle University) & David Stephan (Two Bridges Instructional Technology) presented A Course in Data Discovery & Predictive Analytics. Slides.  Presents general principles of using big data and data discovery; includes a detailed week by week list of topics and recommended software for the course. 

Mark Berenson

Statistics Course for Big Data & Analytics. slides
Big Data Implications for Stat Analysis & Instruction slides

"The time has come for AACSB-accredited undergraduate programs to include a core-required course in Business Analytics as a sequel to a course in Business Statistics."

Introductory Statistics

Webster West: What Should We Teach in an Intro Stat Course?  slides
Amy Phelps: Write What? I thought this was a Math class.      Slides

Mark Eakin:  Simplifying Framework for an Intro Stats Class.  Slides

Other Topics

Norean Sharpe: Does AP Exam Credit Have an Impact on GPA?  slides
Aric LaBarr: Analytics Education and the Evolving Workforce  Slides
M Gisela Bardossy: Mini-Cases using Baltimore ... Indicators  slides

 Statistical Publications & Journals: 2014

Significance Magazine

Jan: The Timeline of Statistics by Julian Champkin.

Feb: The Palma measure of income inequality - Alex Cobham, Andy Sumner 

Feb: Even birds follow Pareto's 80–20 rule - Rispoli, Zeng, Green & Higbie

Feb Visual: The champagne glass effect. J. Champkin

Feb: North Americans – one third of world's weight?: Obesity and the comma - Stella Dudzic

Teaching Statistics:

Summer: Regression Analysis and the Sociological Imagination by Fernando De Maio. 

Summer: Monty's dilemma with no formulas. Ruma Falk

Fall: Developing Consistency in the Terminology and Display of Bar Graphs and Histograms by Patricia B. Humphrey, Sharon Taylor and Kathleen Cage Mittag.

Significance Magazine (continued)

Oct:  Does New York City really have as many rats as people? by Jonathan Auerbach

Oct: A world without statistics by Andrew Gelman.

Dec: Cutting through the numbers Statisticians need to prioritise clear communication over numerical detail, says Ed Swires-Hennessy as he discusses his new book, Presenting Data, with Allan Reese. 

CHANCE Magazine: Howard Wainer

11/20: Visual Revelations: Happiness & Causal Inference

9/24: Musing About Changes in the SAT: Is the College Board Getting Rid of the Bulldog?

4/16: Life Follows Art: Gaming the Missing Data Algorithm

2/13: On the Crucial Role of Empathy in the Design of Communications: Genetic Testing as an Example


Building Capacity for Developing Statistical Literacy in a Developing Country: Lessons Learned from an Intervention by Delia North (right), Iddo Gal, and T. Zewotir.

When Statistical Literacy Really Matters: Understanding Published Information about the HIV/AIDS Epidemic in South Africa by Sally Hobden.

Call for Papers: Research on Statistical Literacy


Exploiting Lexical Ambiguity to Help Students Understand ... Random by Kaplan (right), Rogness & Fisher. 

Use of Data Visualisation in the Teaching of Statistics by Forbes, Chapman, Harraway, Stirling, and Wild. 

Middle School Students’ Statistical Literacy: Role of Grade Level and Gender by Ayşe Yolcu


Statistical Literacy and Data Literacy

Data Interpretation in the 21st Century: Issues in the Classroom by James Nicholson and Gerry Mulhem. 10/2014.

Simpson's Paradox


ICOTS in 2014

ICOTS-9 in Flagstaff, AZ

Great keynote! What can we learn from real-world communication of risk and uncertainty? by David Spiegelhalter (and Jenny Gage).  

Statistical Literacy was a dominant topic at ICOTS-9.   Proceedings.

Topic 7, Statistical literacy in the wider society, was organized by Bob del Maas (US), Sebastian Kuntze (Germany) and Michiko Watanabe (Japan).  

7A: Statistical literacy beyond the Classroom
Organized by Carl Lee.

7A1: Odyssey: A Journey to Lifelong Statistical Literacy by Milo Schield  Slides.

7A2: Teaching statistics for engagement beyond classroom walls by Larry Lesser.

7A3: Taking statistical literacy to the masses with YouTube, blogging, Facebook and Twitter by Nicola Petty Ward

7B: Statistical literacy requirements for teachers

7B1: Statistical literacy requirements for teachers: Jeffrey Hovermill, Brian Beaudrie, Barbara Boschmans

7B2: Developing statistical knowledge for teaching of variability through professional development: Helena Wessels

7B3: Teachers’ views related to goals of the statistics classroom – from global to content-specific: Sebastian Kuntze

7C: Assessing Statistical literacy

7C1: Towards statistical literacy - relating assessment to the real world: Penelope Bidgood

7C2: Establishing the validity of the LOCUS assessments through an evidenced-centered design approach: Tim Jacobbe, Catherine Case, Douglas Whitaker, Steve Foti

7C3: Sufficiently assessing teachers’ statistical literacy: Helen Chick, Robyn Pierce, Roger Wander

7D: Developing Statistical literacy

7D1: Students’ beliefs about the benefit of statistical knowledge when perceiving information through daily media: Alexandra Sturm, Andreas Eichler

7D2: Changing the course: from boring numeracy to inspiring literacy: Kimmo Vehkalahti

7D3: A numeracy infusion course for higher education (NICHE): strategies for effective QR instruction: Esther Isabelle Wilder, Elin Waring, Frank Wang, Dene Hurley

7D4: Implementing a quantitative literacy core competency requirement in the College of Arts and Science at Miami University: John Bailer

7E: Factors that Affect Statistical Literacy

7E1: Critical thinking as an impact factor on statistical literacy – theoretical frameworks and results from an interview study: Einav Aizikovitsh-Udi, Sebastian Kuntze

7E2: A multilevel perspective on factors influencing students’ statistical literacy: Ute Sproesser, Sebastian Kuntze, Joachim Engel

7E3: Sustaining communication of the value of statistics in the humanities: Nicole Mee-Hyaang Jinn

7F: Factors that Affect Statistical Literacy

7F1: Reconceptualizing statistical literacy: Developing an assessment for the modern introductory statistics course: Laura Ziegler

7F2: Improving statistical literacy through supplemental instruction: Alexandra Kapatou

7F3: Interpreting variation of data in risk-context by middle school students: Antonio Orta, Ernesto Sánchez

9C:  Big Data and Data Science for Education

9C1: Exploring “white flight” via open data and big data: James Ridgway, James Nicholson, Sean McCusker

9C2: Teaching data science to teenagers: Amelia McNamara, Mark Hansen

9C3: Integrating big data into the science curriculum: Daniel Kaplan, Paul Overvoorde, Elizabeth Shoop

ECOTS in 2014

Breakout Sessions

Statistics for the 21st Century: Are we Teaching the Right Course? Richard De Veaux and Daniel J. Kaplan (left)

Two Big Ideas for "Big Data" Analytics. Schield paper.

How Introductory ,, Statistics .. Instructors Can Introduce Big Data through Four of its Vs  John McKenzie

Panel: Teaching from Big data.   Schield slides.

Poster: Ensuring Statistical Literacy for Pre-Service Education Majors Stacy M. Bjorkman & Kelly H. Summers

Poster: Use of Gapminder.org in Introductory Statistics to Bridge Across Disciplines Dai-Trang Le, UCLA

Poster: Integrating Writing in the Statistics Curriculum Dean Poeth & Jane Oppenlander, Union Graduate College.

Poster: Stay Calm and Think Critically: Student Perceptions of Numbers in Introductory Statistics.  Marc Isaacson, Augsburg College

ASA JSM in 2014


Five papers in the Proceedings included "confound" in their title or abstract.   Eight papers included "statistical literacy" (one of these is Schield).  52 included "caus" (e.g., cause, causal, etc.)

JSM Published Papers In Process


  • 2014: The Importance of Statistics by RSS GetStats Board Members.  RSS Get Stats: Influencing Change -- Statistical Literacy

  • 2014 Dec 23:  Bob Hogg: A Statistical Giant.   RIP.

  • 2014 Nov 13:  Meet Common Core Standards with Statistics.  Posted by Jeff Wyman on November 13th, 2014.  Copy

  • 2014 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 (over 4,000 times in May-Nov 2014).   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). 

  • 2014 April. Willful Ignorance: The Mismeasure of Uncertainty by Herbert Weisberg.  Available 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!"  

Conferences in 2014

  • 2014: July 7-11. 2014 IMS Annual Meeting  Sydney, Australia

  • 2014 June 1. Rethinking Undergraduate Business Education: In the Classroom and BeyondDSI Journal of Innovative Education. Call for papers: June 1.

  • 2014:  May 19-23.  eCOTS: Electronic Conference on Teaching Statistics.   Program
    Presentation sessions should address one of the three themes:  (1) Teaching from Big Data:  What are some of the issues and challenges when it comes to using big data for teaching and learning purposes? How can a focus on big data change the way we teach statistics? How can we teach data analytic methods that draw insights from massive data?   (2) The Impact of the Common Core: How can we better prepare, at the college level, future teachers of statistics at all levels (K-16)? How must teachers be prepared to deal with the Common Core State Standards? Further, how should the teaching of statistics at the college level change in light of changes in the K-12 statistics curriculum?  (3) Bridging the Disciplines:  How can we enhance the centrality of statistics across the disciplines? What can we learn from and take from other disciplines in order to create a more positive learning experience for our students? How can we connect with other disciplines and forge relationships with these disciplines that will be mutually beneficial? How might we create valuable learning experiences for students that will prepare them to work in multidisciplinary teams? 

    1) Keynotes:
    Mon 11  Preparing K-12 Teachers to Navigate the Data Stream: Great Opportunities and Challenges with Christine Franklin, Univ of Georgia
    Wed 11 Fundamentally Changing Maths Education for the New Era of Data Science with Conrad Wolfram, The Wolfram Group

    2) Selected Breakout sessions on Teaching from Big Data: (All times are Eastern Daylight Time)
    Mon  15:30 "Big Data, Data Science and Next Steps for the Undergraduate Curriculum" with Nicholas J. Horton, Amherst College
    Tues 11:30 "How Introductory Applied Statistics Course Instructors Can Introduce Big Data through Four of its Vs". John McKenzie, Babson College
    Tues  2:30 Two Big Ideas for Teaching Big Data: Coincidence and Confounding by Milo Schield.   Slides  Data
    Wed 10:00  "Statistics for the 21st Century: Are we Teaching the Right Course?"  Richard Deveaux, Williams & Daniel J. Kaplan, Macalester
    Wed 14:15  "Panel on Big Data": Nicholas Horton, Amherst; Daniel Kaplan, Macalester; Mine Cetinkaya-Rundel, Duke; John McKenzie, Babson; Milo Schield, Augsburg Slides.

    3) Selected Virtual Posters:
    Ensuring Statistical Literacy for Pre-Service Education Majors Stacy M. Bjorkman, Walden U. & Kelly H. Summers, N. Illinois U.
    Stay Calm and Think Critically: Student Perceptions of Numbers in Introductory Statistics by Marc Isaacson, Augsburg College  Slides
    Abstract:  Students entering an introductory statistics course bring a number of attitudes and perceptions regarding statistics encountered in our daily life. Some students arrive awestruck by numbers while others tend to be completely cynical of any number no matter its source. This poster will present the findings of 2 sets of surveys. One regarding the perceptions of incoming introductory statistics students and the other a group of over 100 statistical educators surveyed in 2012 regarding the perceptions of their students. While large numbers of students admitted to being at either end of the spectrum from being naive about numbers to completely distrustful of all statistics, over 80% of statistical educators stated that an introductory course learning objective should include moving students towards the middle of this spectrum with the goal of being a critical thinker regarding statistics. Recommendations regarding revised learning objectives for the introductory course and course revisions will be discussed.

    Tues 2:30: Two Big Ideas for Teaching Big Data: Coincidence and Confounding by Milo Schield.  DESCRIPTION: Coincidence and confounding are two statistical influences that dominate when dealing with “big data.” These ideas are being taught in Augsburg’s “Statistical Literacy for Managers” course using Excel.  Participants will access Excel worksheets demonstrating the Law of Very Large Numbers (as data size increases, the unlikely becomes almost certain).  Participants will analyze data showing a sign-reversal after controlling for a confounder.  Participants will examine the claim that confounding is incidental in forecasting, but is essential in causal exploration.  Engagement: Participants will be encouraged to (1) form generalizations on the influence of confounding and coincidence as the number of data records increases and (2) discuss the importance of teaching these ideas in introductory statistics.  Take-away: Participants should have a better idea of what might be taught when dealing with big data in introductory statistics.    Slides  Data

  • 2014 April 15. Added new page for Herbert I. Weisberg at StatLit.org.

  • 2014 March.  Epidemiology as a liberal art: from graduate school to middle school, an unfulfilled agenda by Michael B. Bracken (Yale). Annals of Epidemiology 03/2014; 24(3):171-3

  • 2014 March 3. Added new page for Judea Pearl at StatLit.org

  • 2014 January 18. Added new page for Wayne Winston at StatLit.org

  • 2014: Jan 15-18. 2014 Joint Mathematics Meeting, Baltimore, MD. 
    Note: Paper titles never mention "confound", "confounds" "confounding", "confounder", "cause" , "causes" or "causing."
    Just one paper title mentions "causal": Mathematical Challenges in Causal Inference ...."

    WEDNESDAY: Assessing Quantitative Reasoning and Literacy, organized by Semra Kilic-Bahi, Eric Gaze and Aaron Montgomery:
    8:00 a.m. Standardizing assessment across QL courses. Jill Bigley Dunham and Betty Mayfield*, Hood College
       8:20 a.m. Three Approaches to Assessment in the Quantitative Reasoning Classroom. Maura B. Mast*, University of Massachusetts Boston
       8:40 a.m. Assessing Quantitative Reasoning in Introduction to Probability and Statistics. Robert J. Krueger*, Concordia University, St. Paul
       9:00 a.m. Collaborative approach to Assessing Q/L within Carnegie's Quantway. Cinnamon Hillyard*, Eugene Milman and Duane Benson
       9:20 a.m. QL Across the Curriculum at Colby-Sawyer College. Semra Kilic-Bahi*, Colby-Sawyer College
       9:40 a.m. Measuring Habits of Mind: Toward a Prompt-less Instrument for Assessing Q/L. Stuart Boersma* and Dominic Klyve
      10:00 a.m. Results from an NSF TUES Quantitative Reasoning Assessment Project. Eric Gaze*, Bowdoin College
      10:20 a.m. Assessment in an inquiry-based quantitative reasoning course for business students. Victor I Piercey*, Ferris State University
      10:40 a.m. The Need to Assess Quantitative Literacy in the Major. Rodney E McNair*, Delaware State University

    RIDAY: Data, Modeling, and Computing in the Introductory Statistics Course, organized by Zieffler, Alberts and Pruim
      1:00 p.m. Data Visualization Using Minitab, Google Fusion Tables, and Tableau. Sue B Schou*, Idaho State University
      1:20 p.m. Visualizing the Central Limit Theorem through Simulation. Eric Ruggieri*, College of the Holy Cross
      1:40 p.m. P-Values Through Simulation. Julie A. Belock*, Salem State University
      2:00 p.m. Understanding P-values: Advantages & Challenges of Randomization-Based Inference. Catherine Case, M. Battles, T. Jacobbe
      2:20 p.m. Playing and Getting "Messy" with Data. Rodney X. Sturdivant*, Shonda Kuiper, and Kevin Cummiskey
      2:40 p.m. Designing Simulated Experiments in the Introductory Statistics Course. Shonda R Kuiper*, Grinnell College
      3:00 p.m. Using an Ever-Growing Data Set in an Introductory Statistics Course. Sarah L. Mabrouk*, Framingham State University
      3:20 p.m. Big Data in the Intro Stats Class: Expose Students to a Real-World, Complex Dataset. Nicholas J. Horton, B. Baumer, H. Wickham
      3:40 p.m. Statistical Crowd Counting. Grant L Innerst*, Shippensburg University Ben Galluzzo, Shippensburg University
      4:00 p.m. Using Genomics Data in Introduction to Probability and Statistics. Kimberly A Roth*, Juniata College
      4:20 p.m. Predicting Drug Resistance: Probability and Statistics Meet the Building Blocks of Proteins. Majid Masso*, George Mason University
      4:40 p.m. Modeling -- It's harder than you might think. Patricia B Humphrey*, Georgia Southern University
      5:00 p.m. Against All Odds: Inside Statistics. Marsha J. Davis*, Eastern Connecticut State University
      5:20 p.m. Using Faculty Research as a Teaching Tool In Statistics. Phong Le*, Niagara University
      5:40 p.m. A Semester Project for Introductory Statistics. Murray H. Siegel*, Arizona State University

    FRIDAY: Instructional Approaches to Increase Awareness of the Societal Value of Mathematics
      1:00 p.m. Graph clustering for the high school classroom. Emilie Hogan* and Gabriela Radu
      1:20 p.m. Using material from a standard college algebra course to enhance students understanding of some social issues. A. S. Elkhader
      1:40 p.m. College Algebra or Economics of Being Green. Yevgeniy V. Galperin*, East Stroudsburg University
      2:00 p.m. A Service-Learning Approach to Mathematical Modeling. Olivia M. Carducci*, East Stroudsburg University
      2:20 p.m. Supporting Quantitative Literacy with Service-Learning: The Pitfalls and the Promise. Victor I Piercey*, Ferris State University
      2:40 p.m. Using Service-Learning to Connect a Quantitative Literacy Course to the Community. Andrew J Miller*, Belmont University
      3:00 p.m. Building a capstone course on the theme of the relevance of mathematics to society. Maritza M. Branker*, Niagara University
      3:20 p.m. Math in the City: connecting classroom to community through modeling. Alexandra Seceleanu*,  Kathryn (Katie) Haymaker

Citations as of 2013

Google Scholar search for the phrase "statistical literacy":  3,790 entries excluding patents and citations as of Dec., 2013. 

For this list, select if "Statistical Literacy" in Title.  Total number by Year of Publication: 1951 (1). 1979 (2). 1989 (1). 1992 (1). 1993 (1). 1995 (3). 1997 (3). 1998 (5). 1999 (4). 2000 (8). 2001 (3). 2002 (15). 2003 (13). 2004 (13). 2005 (12). 2006 (12). 2007 (6). 2008 (12). 2009 (3). 2010 (20). 2011 (6). 2012 (1). 2013 (1).

RANK "--------------------- CITATIONS -----------------------
2013 2013 2012 2011 Article/Book
1 406 307 265 I. Gal (2002).  Adults' statistical literacy: Meanings, components, responsibilities. ISR
2 165 131 106 K Walman (1993).  Enhancing statistical literacy: Enriching our society.  JASA
3 142 123 100 J Watson, R Callingham (2003).  Statistical literacy: A complex hierarchical construct.  SERJ
4 134 108 86 DJ Rumsey (2002).  Statistical literacy as a goal for introductory statistics courses.   JSE
5 105 56 56 D. Ben-Zvi (2004).  Statistical literacy, reasoning, and thinking: Goals, definitions, and challenges.
6 98 80 66 D Ben-Zvi, et al. (2004).   The challenge of developing statistical literacy, reasoning, and thinking. [book]
7 65 51 36 I Gal (2005).  Statistical literacy.  The Challenge of developing statistical literacy
8 48 45 39 Watson & Moritz (2000).  Development of understanding of sampling for statistical literacy.  Jrnl Mathematical Behavior
9 44 37 33 J Garfield et al, (2005).  Research on statistical literacy, reasoning, and thinking....  The challenge …
10 40 36 31 J Watson (2005).  Developing reasoning about samples.  The challenge of developing statistical literacy.
11 36 32 30 S. Murray and I. Gal (2002). Preparing for diversity in statistics literacy: Institutional-educational implications
12 31 30 27 I Gal (2003).  Teaching for statistical literacy and services of statistics agencies.  American Statistician
13 30 25 23 I. Gal (2002).  Statistical literacy: Conceptual and instructional issues.  Perspectives on adults learning mathematics
14 30 28 23 M. Schield (1999).  Statistical literacy: Thinking critically about statistics.  APDU: Of Significance
15 29 28 24 M. Schield (2004).   Statistical literacy curriculum design.   IASE Curriculum Design Roundtable.
16 28   15 M. Schield (2004).  Information literacy, statistical literacy and data literacy.  IASSIST
17 28 25 22 R. Callingham, J. Watson (2005).  Measuring statistical literacy.  Journal of Applied Measurement
18 24 23 22 I Gal (1995).  Statistical Tools and Statistical Literacy: The Case of the Average.  Teaching Statistics.
19 24     I. Gal (2003).  Expanding conceptions of statistical literacy. SERJ
20 24     M Schield (2006).  Statistical Literacy: Reading graphs and tables of rates and percentages
21 24  


M. Schield (2002).  Statistical literacy survey analysis: Reading tables and graphs of rates and percentages
22 23     K. Bessant (1992).  Instructional design and development of statistical literacy.
23 22     Hellems et al (2007).  Statistical literacy for readers of Pediatrics: a moving target
24 22     M. Schield (2010).  Assessing statistical literacy: Take CARE.  In Assessment Methods… book.
25 20     DG Haack (1979).  Statistical literacy: A Guide to Interpretation.  Book.
26 19     M. Schield (2000).  Statistical literacy: difficulties in describing and comparing rates and percentages
27 18     Snell (1999).  Using Chance media to promote statistical literacy
28 17     JM Watson (2004).   Statistical literacy: From idiosyncratic to critical thinking
29 16     Anyama & Stevens (2003).  Graph interpretation aspects of statistical literacy: A Japanese perspective
30 15     J. Moreno (1998).  Statistical literacy: statistics long after school
31 15     JL Moreno (2002).  Toward a statistically literate citizenry: What statistics everyone should know
32 15     M. Schield (2002).  Three kinds of statistical literacy: What should we teach
33 14     JM Watson (2003).  Statistical literacy at the school level: What should students know and do
34 14     M. Schield (2004).  Statistical Literacy and liberal education at Augsburg College [citation]
35 13     Lehola (2003).  Promoting statistical literacy: A South African perspective
36 13     P. Cerrito (1999).  Teaching statistical literacy
37 11     JM Watson (1995).  Statistical literacy: A link between mathematics and society
38 10     Carmichael & Cunningham (2003).  Factors Influencing … Students' Interests in Statistical Literacy
39 10     Gelman et al. (1998).  Student projects on statistical literacy and the media
40 10     JM. Watson (1998).  The role of statistical literacy in decisions about risk: Where to start
41 10     Watson & Kelly (2000).  The vocabulary of statistical literacy
42 9     Ridwgway et al. (2008).  Mapping New Statistical Iliteracies and Literacies
43 8     M. Schield (1998).  Statistical literacy and evidential statistics
44 8     Monahan (2007).  Statistical Literacy A Prerequisite for Evidence-Based Medicine
45 8     Watson & Nathan (2010).   Assessing the interpretation of two-way tables as part of statistical literacy
46 7     D. Trewin (2005).  Improving statistical literacy: The … roles of schools and the National Statistical Offices
47 7     DJ Rumsey (2002).  Statistical literacy: Implications for teaching, research, and practice
48 7     Kurtz et al. (2008).  Using models and representations in statistical contexts:....sub-competency of statistical literacy
49 7     M. Schield (2000).  Statistical literacy and mathematical reasoning
50 7     R. delMas (2002).  Statistical literacy, reasoning, and thinking: A commentary



Lifetime page views (Only those with over 10,000 page views).

  1. 221,442: Index or Home page (2003-)

  2.   38,935: Standardizing (2006-)

  3.   31,171: Joel Best (2006-)

  4.   25,881: Articles/Papers (2006-)

  5.   24,162: Adult Numeracy (2008-)

  6.   21,030: Howard Wainer (2007-)

  7.   16,708: StatLit News 2008 (2009-)

  8.   16,311: StatLit News 2009 (2008-)

  9.   15,156: StatLit News 2007 (2007-)

  10.   12,729: StatLit News 2005 (2006-2008)

  11.   11,388: StatLit News 2010 (2011-)

StatLit.org has had more than a 1.7 million downloads, 1.4 million visits and 930,000 page views between 2005 and 2014.

Lifetime paper downloads (Only those with over 10,000 downloads)

  1. 100,052: M. Schield (2006) Percentage Graphs in USA Today

  2.  17,907: M. Schield (2006) Presenting Confounding Graphically

  3.  10,933: Jane Miller (2009) Interpreting ... regression coefficients

  4.  10,038: M. Schield (2011) Stat Lit: New Mission for Data Producers


EXCEL WORKSHEET DEMOS.  All by Milo Schield (2014 downloads)

  1. Create lognormal in Excel 2013. (36,618+585) Slides Demo

  2. Model Logistic Regression using Excel 2013 (6,472+806)  6up 1up

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

  4. COUNTIF histograms: Excel 2013 (3278+730) 6up 1up demo

  5. Confidence intervals with Excel 2010 (2044+1861) 6up 1up

  6. T-Test command with Excel 2013 (294+2,283) 6up 1up

  7. Trendline 2Y1X with different scales. (641+1834)   6up  1up

  8. Create Pivot Tables using Excel 2008 (566+1334) 6up 1up

  9. Using the T-Test function in Excel 2008 (1563+). 6up 1up

  10. Regress using Data Analysis in Excel 2013 (508+) 6up 1up

  11. Create lognormal distribution with Excel 2008. (466)  6up

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

AUDIO CHAPTER OVERVIEWS.  All by Milo Schield (2014 downloads)
Reviews of chapters in Schield's Statistical Literacy textbook.

  1. StatLlit Text Ch 4 Overview 6up  1up  Audio (1998).

  2. StatLlit Text Ch 3 Overview 6up  1up  Audio (465). 

  3. StatLlit Text Ch 6 Overview 6up  1up  Audio (336).

  4. StatLlit Text Ch 5 Overview 6up  1up  Audio (307).


DeepMetrix tracks the top 25 files downloaded each month from StatLit.org. Very few files appear in the top 25 all 12 months.  The number of months tracked is in brackets [#] if less than 12.

Excludes papers having fewer than 300 downloads. Excludes non-articles such as Amazon lists, reference documents (QR and statistical textbooks) and non-statistical articles (Freeminds).  Unlike previous years, it includes PowerPoint slides and selected reference documents (UTSA-QEP-quantitativeScholarship-Final.pdf) and pdf-scans (1993 Weinberg). 


Top Pages Viewed at www.StatLit.org in 2014
(####; ####; ###; ###): page views 2014, 2013;...2010; 2009; 2008.
  1. Index (50,347; 47,674; 29,554; 28,157, 23,159; 15,729; 10,423)

  2. Standardizing (6711; 9809; 6633; 5176; 3265; 2434; 1718)

  3. StatLit News 2013 (4,099)

  4. StatLit News 2012 (3539; 2891; 1297[7])

  5. Joel Best (3530; 3451; 4617; 5036; 4794; 3481; 3118): Author

  6. StatLit Papers (3175; 2914; 3073; 4203; 3131; 2837; 2444)

  7. StatLit News 2009 (3148; 2269; 2797; 3228; 4869)

  8. StatLit News 2010 (2896; 2836; 2693; 2963)

  9. Q/L Textbooks (2687*; 1868*; 2233; 3159; 2741; 2484; 2387)

  10. StatLit News 2011 (2596; 2562; 3023)

  11. Howard Wainer (2574; 3396; 4296; 3893; 2778; 2127; 1966)

  12. StatLit News 2008 (2567; 2501; 2698; 2975; 3333; 2634)

  13. Adult Numeracy (2489; 2784; 4070; 4998, 5007; 2467; 1987)

  14. Tools (2039[10])

  15. StatLit News 2007 1584*; 1527*; 1940; 2127; 2552; 1498; 1928

  16. Blastland (1818*; 1331* [9]) Author of "The Tiger that Isn't"

  17. Q/L Activities QL2 (1605*; 1886; 2106; 1725*; 1278; 1378)

  18. Gerd Gigerenzer (1586*; 1713*; 2283; 2567; 1993*; 1415; 1503)

  19. Q/L Books QLit (1522*; 1884; 2305; 1418; 1459) No textbooks

  20. Jane Miller (1808*) Chicago Guides

  21. Wayne Winston (1105*)  Textbook author: Excel Statistics

  22. Gerald Bracey (897*; 1487; 1923; 2374; 2655; 2669; 2,035)

Total 2013 page views (including /GC): 153,099 -- a 19% increase.

[Left side is OK for 2014; Right side not updated]

Page views as a percentage of Total:  Index (31%), Standardizing (6%), Joel Best (2%), Howard Wainer (2%), StatLit Papers (1.9%) and Adult numeracy (1.8%). All the rest were less that 1.9% except "Other" (29%).

Six new pages in 2013: Uri Bram, Conrad Carlburg, Kaiser Fung, David Moore, StatLit2013 and Video1.

Note: Website statistics are tabulated by the DeepMatrix program LiveStats® .XSP V8.03. Each month, the views for the top 25 website pages are tabulated.  Those pages that aren't in the top 25 that month are treated as having zero views. 

* Pages with less than 12 months statistics are indicated by the asterisk (no adjustment). Pages with less than 6 months of statistics are omitted (except those that are student assigned during certain months).

In 2013, the StatLit web site has 69 htm pages in the main directory. Others include student-assigned pages (/GC) and the Keck Survey.

Navigation page views (2013; 2012; 2011; 2010; 2009; 2008) totaled (13,327; 10,203; 11,180; 9,716; 9,522; 8,474): Statistical Literacy (2,482; 2,616; 3,046; 2,729; 2,396; 2,100), Statistical Reasoning (3,829; 2,081; 2,051; 1,617*; 1,625; 1,425), StatLit News (2,087; 1,980*; 2,162; 1,836; 1,928; 1,863), Authors (1,715*; 1,578*; 2,245; 1,980; 2,033; 1,860), Numeracy (1,937*; 1,533*; 1,676*; 1,554*; 1,540; 1,226) and 2Authors2 (1277*; 415*[3]).

Student-assigned page-views [*.xls and /GC] were not totaled.    

This site was last updated 10/25/22