Website Highlights: 11th Year Anniversary

• StatLit.org still growing:  Index views up 61%; Page views up 19%; Downloads up 8%; Visits up 5%.  More than 265,000 downloads, 190,000 visits, 150,000 page views  and 47,000 home page views.
• 4 new pages: Uri Bram, Conrad Carlburg, Kaiser Fung and David Moore
• Google ranked StatLit.org #2 for “statistical literacy” (Wikipedia as #1)
• New records:  StatLit.org has had more than a MILLION downloads, 950,000 visits and 710,000 page views inception-to-date (2004-2013).

Editor: Best New Trade/Professional Books in 2013

• Naked Statistics: Stripping the Dread from the Data by Charles Wheelon
• NumberSense: How to Use Big Data to Your Advantage by Kaiser Fung
• “Raw Data” Is an Oxymoron edited by Lisa Gitelman
• Math on Trial: Numbers Used … in the Courtroom by Schneps & Colmez
• The New York Times Book of Mathematics: More Than 100 Years of Writing by the Numbers edited by Gina Kolata.
• Risk, Chance and Causation: Origin/Treatment of Disease by M. Backken

Editor: Top Papers/Journal Articles in 2013

• Using Differential Comparisons in Observational Studies by Paul Rosenbaum in Chance magazine
• Open Data, Official Statistics and Statistics Education: Threats and Opportunities for Collaboration by Jim Ridgway & Alan Smith — IASE Keynote
• Using a Media-Article Approach to Quantitative Reasoning as an Honors Course: An Exploratory Study by Stuart Boersma & Dominic Klyve
• Using context to classify variables by Lawrence M. Lesser — Teaching Stats
• Simpson's paradox in psychological science: a practical guide by Kievit et al. — Frontiers in Psychology, 4, 513

Editor: Top New Conference Papers in 2013

• 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 the beginning of statistics education for the 21st century.” — Milo Schield, Editor: StatLit.org.]

• JSM attendees ranked this paper #4 out of 35:  Statistical Education: Steadfast or Stubborn? by Milo Schield  1up
• Smith: Six Types of Data Analytics   (one page summary)

Top 12 Most Downloaded Articles from StatLit.org in 2013

1. Percentage Graphs in USA Today — Milo Schield 2006 ASA Proceedings.  (7771; 17,819; 19,114; 11,179; 13,253; 14,247; 8809) Total: 93,216
2. Statistical Literacy: Uses & Abuses of Numbers by Andrew Nelson  6up  (4,912)
3. Presenting Confounding Graphically Using Standardization by Milo Schield — 2006 STATS magazine (3709 [11]; 4646; 1289; 2084; 1985; 1616). Total: 15,329.
4. Statistical Literacy: A New Mission for Data Producers by Milo Schield.  2011 SJIAOS (3104 [8]; 2815 [10]; 1723).  Total: 7,642
5. Univ. Texas San Antonio: Quantitative Scholarship — Final Draft   Press release 2009  (1896 [4])
6. Statistics for Political Science Majors  Gary Klass 2004 ASA (1817; 1416[10]; 1389[10]; 596[6]; 765; 215)
7. Interpreting the substantive significance of multivariate regression coefficients   Jane Miller 2008 ASA  (1,630 [9]; 3,118; 1625[11]; 2094; 1412).

8. Interpreting the Cumulative Frequency Distribution of Socio-Economic Data   Othmar Winkler  (2009 ASA [1,515 [11]; 822[7])
9. Random Sampling versus Representative Samples by Milo Schield.  1994 ASA  (1,328)  [This was the first paper given by Schield at JSM.  In the Q&A following his talk, the first respondent said “I have authored many papers in statistics, and I maintain that you, Sir, are undermining the theoretical foundations of our discipline.”  The next respondent said “This is good paper; we need more of this kind of thinking.”]
10. Assessing Students’ Attitudes: The Good, the Bad, and the Ugly by Anne Millar and Candace Schau  2010 ASA  (1,024 [6])
11. Coincidence in Runs and Clusters  Milo Schield 2012 MAA  (915 [5]; 2,466[9])
12. Making Statistics Memorable: New Mnemonics and Motivations by Larry Lesser.  ASA 2011.  (900 [8])

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™.

2013: Volume 6, Issue 1

• Editorial: The Scope of Numeracy after Five Years by Vacher and Wallace
• Dyscalculia: Characteristics, Causes, and Treatment by Price and Ansari
• Personal Financial Behavior: QL and Material Values by Nye & Hillyard
• Quantitative Reasoning Learning Progressions for Environmental Science: Developing a Framework by Mayes, Peterson, and Bonilla
• Using a Media-Article Approach to Quantitative Reasoning as an Honors Course: An Exploratory Study by Stuart Boersma and Dominic Klyve
• Notes: The Problem of Too Many Statistical Tests: Subgroup Analyses in a Study Comparing Effectiveness of Online and Live Lectures by David Lane
• Column: Parts of the Whole: When Variation is the Goal by D. Wallace

2013 Volume 6, Issue 2: Financial Literacy

• Editorial: Financial Literacy and Quantitative Reasoning in the High School and College Classroom by Annamaria Lusardi & Dorothy Wallace
• The Geography of Financial Literacy: Bumcrot, Lin, and Lusardi
• Financial Literacy and Credit Card Behaviors by S. Allgood & W. Walstad
• In Our Best Interest: Women, Financial Literacy, and Credit Card Behavior by Gary R. Mottola
• Financial Literacy and Financial Behavior among Young Adults: Evidence and Implications by Carlo de Bassa Scheresberg
• Financial Literacy and Retirement Planning in Switzerland, Brown & Graf
• Financial Literacy and Retirement Planning in Australia by Julie R. Agnew, Hazel Bateman, and Susan Thorp
• Financial Literacy and Financial Planning in France by Luc Arrondel, Majdi Debbich, and Frédérique Savigna
• Financial Literacy and Household Savings in Romania by E. Beckmann
• Making College Count: An Examination of Quantitative Reasoning Activities in Higher Education by Rocconi, Lambert, McCormick & Sarraf
• Does Completion of Quantitative Courses Predict Better Quantitative Reasoning-in-Writing Proficiency? Nathan D. Grawe
• Simplified Data Envelopment Analysis: What Country Won the Olympics, and How about our CO₂ Emissions? by Alexander Vaninsky
• Column: Parts of the Whole: The Educational Sieve by Dorothy Wallace

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…”

Elwert Wins ASA Causality Prize

The ASA awarded the first Causality prize to Felix Elwert (Sociology, UW-Madison) for his innovative two-day course, Causal Inference with Directed Acyclic Graphs.  This graduate course “reviews causal and counterfactual concepts; principles of directed acyclic graphs; nonparametric identification by conditioning; conceptual differences between confounding, over-control, and selection bias; examples and exercises.”

Engaging Mathematics

NSF awards $599,995 to Wesleyan University for Passion-Driven Statistics: A multidisciplinary project-based supportive model for statistical reasoning and application. Disseminating a project-based course that provides greater access to introductory statistics for non-STEM students. PI: Lisa Dierker (left); Co-PI: David Beveridge. Four-year award 1323084

Causal Inference w. Confounding

NSF awards UCLA $299,919 for Causal and Statistical Inference in the Presence of Confounding Factors. Will develop a theory of how confounders affect data and under what conditions unobserved confounders can be corrected. Proposed theory is related to recent developments in understanding sparsity as studied in EE, CS & statistics. PI: Eleazar Eskin; 3 year 1320589

Causal Inference; Obs. Studies

NSF awards $296,587 to the University of Pennsylvania-Wharton for Causal Inference in Observational Studies. The design of an observational study strongly affects its sensitivity to hidden biases. This project investigates four ways that study design can mitigate confounder bias. PI: Dylan Small (left); Co-PI: Paul Rosenbaum — 3 year grant 1260782

Challenge Students w Big Data

NSF awards $600,000 to Jackson State University for Laboratory for Interdisciplinary Statistical Analysis and Mathematical Learning Through Quantitative Exploration of data. Design ways to use big data to educate math-stats undergraduates to confront challenges. PI: Tor Kwembe; Co-PIs: Xing Yang, Zhenbu Zhang, Raphael Isokpehi and Remata Reddy;  Award Number: 1330801

MidSchool Stat. Misconceptions

NSF awards $406,762 to Measured Progress for The MAMMS Project: Measuring and Addressing Middle-Grades Misconceptions in Statistics. Develop diagnostic assessments to identify specific statistical misconceptions (datasets as entities, comparing datasets, and overreliance on the mean procedure), teacher tutorials and activities. PI: Jessica Masters  3-year 1312133

Child Learn: Probability Displays

NSF awards $499,210 to Univ. of Washington for Young Children's Causal Learning from Probabilistic Social and Physical Displays. To investigate whether young children observing a confounded causal system preferentially attribute probabilistic outcomes to variability in social causes or to variability in physical causes. PI: Andrew Meltzoff. Three-year award 1251702

Conditional Inference in Tables

NSF awards $57,049 to Brown University for Conditional Inference Algorithms for Graphs, Tables, and Point Processes. Conditioning on the margins simplifies the statistical challenges, it greatly increases the computational challenges of any associated statistical procedures. This project addresses this problem. PI: Matthew Harrison. Three-year 1309004

Engage Students in QR via Data

NSF awards $199,656 DUE award to Illinois State University for “The use of high-frequency data to engage students in quantitative reasoning and scientific discourse”; PI: Catherine O'Reilly; Co-PIs: Rebekka Darner, Cayelan Carey. One-year grant 1245707

Numeracy & Risk Literacy

NSF awards $49,866 to Michigan Technological University for CAREER: Numeracy and Risk Literacy. This project maps cognitive processes and individual differences linking them with numeracy and risk literacy across diverse populations. PI: Edward Cokely (founder of RiskLiteracy.org). Five-year 1253263

Estimate Causal Impact of Wealth

NSF awards $95,740 to the National Bureau of Economic Research for Collaborative Research: Novel Approaches Toward Estimating the Causal Impact of Wealth. PI: Matthew Notowidigdo. One-year Award Number: 1326722;  NSF awards $96,863 to New York University for the same collaborative Research. PI: David Cesarini. Award Number: 1326635

The Peter Holmes Prize

Teaching Statistics announces the Peter Holmes Prize. “In honour of the journal’s founding Editor, the Peter Holmes Prize will be awarded to the best classroom idea published in Teaching Statistics in a given year.” See Peter's 1986 ICOTS paper, a video of his 2003 talk at Augsburg, and a video of his 2008 ICOTS talk.

Naked Statistics

“Naked Statistics: Stripping the Dread from the Data” by Charles Wheelon, author of “Naked Economics.” $18. “focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis..”  “shows us how … researchers are exploiting … data from natural experiments to tackle thorny questions.”

Cartoon Intro to Statistics

$15 by Grady Kline and Alan Dabney. “most imaginative and accessible introductory statistics course you’ll ever take.” “an irresistible cast” of dragon-riding Vikings, lizard-throwing giants, and feuding aliens.” “teach you how to collect reliable data, make confident statements based on limited information, and judge the usefulness of polls…”

Questions on Quant Interviews

150 Most Frequently Asked Questions on Quant Interviews (Pocket Book Guides for Quant Interviews) by Dan Stefanica, Rados Radoicic and Tai-Ho Wang. “These questions are frequently and currently asked on interviews for quantitative positions, and cover a vast spectrum, from C++ and data structures, to finance, brainteasers, [probability,] and stochastic calculus.”  $27 224 pg.

Forecasting versus Predicting

Upgrading Leadership's Crystal Ball: Five Reasons Why Forecasting Must Replace Predicting and How to Make the Strategic Change in Business and Public Policy by Jeffrey Bauer.
Readers will learn the real-world value of distinguishing between predicting (extrapolating historical trends) and forecasting (estimating the probabilities of possibilities).  $28 168 pages.

NumberSense: Using Big Data

NumberSense: How to Use Big Data to Your Advantage by Kaiser Fung (author of Numbers Rule Your World). “The problem is, the more data we have, the more difficult it is to interpret it.” “Everyone is prone to making critical decisions based on poor data interpretations.” “[E]xplains when you should accept the conclusions of the Big Data ‘experts’ and when you should say, ‘Wait.’”  $18

Stats & Curiosities: Harvard

Stats and Curiosities: From Harvard Business Review by Harvard Business Review.  $12 Packed with interesting associations such as “Larger teams slow processes, develop larger forecasting errors, hamper co-ordination, increase conflicts, and diminish motivation. The ideal team size is two.”  “Reading too much useless information makes people 46% less likely to think clearly.”

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]

Risk, Chance, Causation

Risk, Chance and Causation: The Origin and Treatment of Disease by Michael B. Backen (Yale).  Describes how professional scientists approach questions of disease causation and therapeutic efficacy to provide readers with the tools to help them understand whether warnings of environmental risk are truly warranted, or if claims of therapeutic benefit are justified.  $48 344 pages

New York Times Book of Mathematics

The New York Times Book of Mathematics: More Than 100 Years of Writing by the Numbers by Gina Kolata (Editor) and Paul Hoffman (Foreword).  “110 articles written from 1892 to 2010 that cover statistics, coincidences, chaos theory, famous problems, cryptography, computers, and many other topics.” “a must-have for any math and science enthusiast!”  $13

Math on Trial: # in Courtroom

Math on Trial: How Numbers Get Used and Abused in the Courtroom by Leila Schneps and Coralie Colmez. $19. “ten trials spanning from the nineteenth century to today, in which mathematical arguments were used—and disastrously misused—as evidence.” Shows “how the improper application of mathematical concepts can mean the difference between walking free and life in prison.”

Probably Approximately Correct

Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World by Leslie Valiant.  Publisher: “a unifying theory that will revolutionize our understanding of how life evolves and learns.” Shows “how both individually and collectively we not only survive, but prosper in a world as complex as our own.” “Profound implications.”  $21 HC

Probabilistic Thinking

Probabilistic Thinking: Presenting Plural Perspectives (Advances in Mathematics Education) edited by Egan Chernoff and Bharath Sriraman. “four main perspectives: Mathematics and Philosophy, Psychology, Stochastics and Mathematics Education.” Coordinates “three theoretical perspectives: classical, frequentist, and subjective.” “6 prefaces, 29 chapters and 6 commentaries.”  $171 700 pg.

“Raw Data” is an Oxymoron

“Raw Data” is an Oxymoron edited by Lisa Gitelman.  “eight episodes in history of data from the predigital to the digital. Together they address such issues as the ways that different kinds of data and different domains of inquiry are mutually defining; how data are variously “cooked” in … their collection and use; and conflicts over what … can't be …reduced” to data.”  $27 192 pg

Using Propensity Scores

Using Propensity Scores in Quasi-Experimental Designs by William Holmes.  “examines how propensity scores can be used to reduce bias with different kinds of quasi-experimental designs and to fix or improve broken experiments. Minimal use of matrix and vector algebra, the book covers the causal assumptions of propensity score estimates and their many uses.”  $48 432 pg pb

Uncertainty Quantification

Uncertainty Quantification: Theory, Implementation, and Applications by Ralph Smith.  Increasing emphasis on models requires “quantified uncertainties for large-scale applications, novel algorithm development, and new computational architectures that facilitate implementation of these algorithms.” This book “provides readers with the basic concepts, theory, and algorithms …”  401 pages $67

Error and Uncertainty

Error and Uncertainty in Scientific Practice (History and Philosophy of Technoscience) by Marcel Boumans, Giora Hon and Arthur Petersen (Dec 31, 2013)  Contributors to this volume … compare methodologies and present the ingredients needed for an overarching framework applicable to all.  $67 256 pg

Inferring Probabilities

Tychomancy: Inferring Probability from Causal Structure by Michael Strevens.  “Tychomancy—'the divination of chances'—presents a set of rules for inferring the physical probabilities of outcomes from the causal or dynamic properties of the systems that produce them.” The rules (1) are reliable, (2) are known to everyone, (3) have played a crucial … role” in science.  $34 280 pages

Causality and Statistics

Causality: Statistical Perspectives and Applications (Wiley Series in Probability and Statistics) edited by Berzuin, Dawid and Bernardinell. Collection of seminal contributions by experts including Cox, Sjolander, Dawid, Greenland, Shipster, Arjus, Berzuni, Vanderweele, Vansteelandt, Pearl, Ramsahai, Daniel, Rutter, Rosenbaum, Emsely, Eichler and Bowsher.  $77 416 pg

George Box: Autobiography

An Accidental Statistician: The Life and Memories of George E. P. Box by George E. P. Box.  “Dr. Box taught himself the statistical methods necessary to analyze his own findings when there were no statisticians available to check his work.” Includes “his research with time series analysis, experimental design, and the quality movement.”  $34 304 pages

Understanding Uncertainty

Understanding Uncertainty (Wiley Series in Probability and Statistics) by Dennis V. Lindley.  $106 424 pages; $165.  A consideration of betting, showing that a bookmaker's odds are not expressions of probability; demonstration that significance tests, may be unsound, even seriously misleading, because they violate the rules of probability…”  Revised Edition $106 424 pages

Quant. Finance: Derivatives

An Introduction to Quantitative Finance by Stephen Blyth.  “provide a suitably rigorous yet accessible foundation to tackle problems the author encountered whilst trading derivatives on Wall Street. The book combines an unusual blend of real-world derivatives trading experience and rigorous academic background.”  $32 192 pages pb

Bayes Rule: A Tutorial Intro

Bayes' Rule: A Tutorial Introduction to Bayesian Analysis by James V. Stone.  “Bayes' rule is a cornerstone of modern probability theory.” Shows “how Bayes' rule is actually a natural consequence of commonsense reasoning. Bayes' rule is derived using intuitive graphical representations of probability, and Bayesian analysis is applied to parameter estimation using the MatLab programs provided.”  $23

Think Bayes

Think Bayes by Allen B. Downey. If you know Python and probability, “you’re ready to tackle Bayesian statistics.” “learn how to solve statistical problems with Python instead of mathematical notation; use discrete probability distributions instead of continuous math.” “Once you get the math out of the way, the Bayesian fundamentals become clearer.”  $25 210p pb

Big Data: A Revolution

Big Data: A Revolution That Will Transform How We Live, Work, and Think by Viktor Mayer-Schönberger and Kenneth Cukier.  “A revolution on par with the Internet or perhaps even the printing press, big data will change the way we think about business, health, politics, education, and innovation in the years to come. It also poses fresh threats…”  $21 hc 256 pages

Understanding / Using Analytics

Keeping Up with the Quants: Your Guide to Understanding and Using Analytics by Thomas H. Davenport and Jinho Kim.  “This book promises to become your 'quantitative literacy' guide—helping you develop the analytical skills you need right now in order to summarize data, find the meaning in it, and extract its value.” “How to interpret and communicate analytical results.”  $20 hc

Too Big to Ignore: Big Data

Too Big to Ignore: The Business Case for Big Data (Wiley and SAS Business Series) by Phil Simon.  Geared towards CIOs, CEOs, presidents, and IT professionals. At a high level, the book makes a compelling business case for that which we are calling Big Data. Simon provides commonsense advice for organizations. … Think Big!”  $34 256 pages

Data Science for Business

Data Science for Business: What you need to know about data mining and data-analytic thinking by Foster Provost and Tom Fawcett. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles.  $31

Predictive Analytics

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel and Thomas H. Davenport.  “Rather than a “how to” for hands-on techies, the book entices lay-readers and experts alike by covering new case studies and the latest state-of-the-art techniques.”  320p; $18

Doing Data Science

Doing Data Science: Straight Talk from the Frontline by Cathy O'Neil and Rachel Schutt.  Topics include “Statistical inference, exploratory data analysis, and the data science process; Algorithms; Spam filters, Naive Bayes, and data wrangling; Logistic regression; Financial modeling; Recommendation engines and causality; Data visualization.” Based on Intro to Data Science class.  $27

On Being a Data Skeptic

By Cathy O'Neil.  “The right approach to data is skeptical, not cynical—it understands that, while powerful, data science tools often fail. Data is nuanced, and “a really excellent skeptic puts the term 'science' into 'data science.'” The big data revolution shouldn't be dismissed as hype, but current data science tools and models shouldn't be hailed as the end-all-be-all, either.”  Kindle: Free 256 pages

Data Just Right

Data Just Right: Introduction to Large-Scale Data & Analytics by Michael Manoochehri.  A “completely practical and indispensable guide for every Big Data decision-maker, implementer, and strategist.” “expert approaches to managing massive datasets, visualizing data, building data pipelines and dashboards, choosing tools for statistical analysis.”  $27 256 pages

Statistical Learning with R

An Introduction to Statistical Learning: with Applications in R by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani.  Based on The Elements of Statistical Learning “but at a level accessible to a much broader audience.” “[A]n accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets.”  $62 430 pages hc

Predictive Analytics with R

Modeling Techniques in Predictive Analytics: Business Problems and Solutions with R by Thomas W. Miller.  Addresses “segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis.” “illuminates the use of cross-sectional data, time series, spatial, and even spatio-temporal data.”  $62 hc

PowerPivot for Excel 2010

PowerPivot for the Data Analyst: Microsoft Excel 2010 (MrExcel Library) by Bill Jelen.  “Simple, step-by-step instructions walk you through installing PowerPivot, importing data, using PivotTables with PowerPivot, using super-powerful DAX functions and measures, reporting to print or SharePoint, and a whole lot more. “help you use PowerPivot to get the right answers”  $23 2010 336 pg

DAX for Excel PowerPivot

DAX Formulas for PowerPivot: A Simple Guide to the Excel Revolution by Rob Collie.  “PowerPivot is a free add-on to Excel ... that allows users to produce new kinds of reports and analyses that were ... impossible before, and this book is the first to tackle DAX formulas, the core capability of PowerPivot, from the perspective of the Excel audience.”  $21 239 pg pb. 2012

Meaningful Visualizations

Data Points: Visualization That Means Something by Nathan Yau.  “focusing on the graphics side of data analysis. Using examples from art, design, business, statistics, cartography, and online media, he explores both standard-and not so standard-concepts and ideas about illustrating data.”  320p. $28

Facts are Sacred: Guardian

Facts are Sacred by Simon Rogers, the Editor of The Guardian/Data.  “reveals how data has changed our world and what we can learn from it.” “publishes and analyses seemingly benign data - released under the auspices of transparency - to bring its readers astonishing revelations about the way we live now.” “extensive data visualisations” “beautifully illustrated”  $20 hc

Data Visualization for Web

Interactive Data Visualization for the Web by Scott Murray.  “teaches you the fundamental concepts and methods of D3, a JavaScript library that lets you express data visually in a web browser. Along the way, you’ll expand your web programming skills, using tools such as HTML and JavaScript.” “easy and fun with this practical, hands-on introduction”  pb $20

Cool Infographics

Cool Infographics: Effective Communication with Data Visualization and Design by Randy Krum.  “More than just using pictures or colorful charts, infographics create the type of visual representation that your audience will quickly grasp and remember.” “prepares you for creating compelling infographics for online marketing, business reports, and presentations…”  pb 368 pages $27

WWII Infographic Guide

World War II in Numbers: An Infographic Guide to the Conflict, Its Conduct, and Its Casualities by Peter Doyle.  “uses color graphics and succinct text to tell the key stories of the battles that engulfed the globe and affected virtually everyone alive during the 1940s.” “see the war set out in numbers; tells the story with a new certainty…”

Infographic History of the World

The Infographic History of the World by James Ball and Valentina D'Efilippo.  Reviews: Positive: My wife and I “are both professional historians, and rated it A+.” “James and Valentina present a vast array of complex information in a contemporary and accessible manner.” Negative: “If this was a term paper, Edward Tufte would grade it ‘F.’”

Making Sense of Consumer Data

Digital Marketing Analytics: Making Sense of Consumer Data in a Digital World by Hemann and Burbary.  288 pages “digital marketing analytics is 100% doable, it offers colossal opportunities, and all of the data is accessible to you.” “chop the problem down to size, solve every piece of the puzzle, and integrate a virtually frictionless system for moving from data to decision, action to results!”  $29

Marketing Analytics

Marketing Analytics: Strategic Models and Metrics by Stephan Sorger.  Covers “a wide variety of decision models and metrics Nearly 400 figures. Step-by-step instructions on market segmentation, conjoint analysis, and other techniques. Current examples demonstrating how organizations are applying models and metrics.”  $45 498 pages

Practioner Guide to Biz Analytics

A Practioner's Guide to Business Analytics: Using Data Analysis Tools to Improve Your Organization’s Decision Making and Strategy by Randy Bartlett.  Effectively integrating analytics into everyday decision making, corporate culture, and business strategy is a multifront exercise in leadership, execution, and support.” Presents “specialized tools and skill sets required to succeed” $41 256 p.

Business Intelligence — Analytics

Business Intelligence in Plain Language: A practical guide to Data Mining and Business Analytics by Jeremy Kolb.  “learn about Business Intelligence, Data Mining, Data Warehousing, Data Discovery, Big Data, Outlier Detection, Pattern Recognition, Predictive Modeling, Data Transformation and much more” “your practical guide to understanding and implementing Business Intelligence.”  66 pg. $7

Predictive Business Analytics

Predictive Business Analytics: Forward Looking Capabilities to Improve Business Performance by Lawrence Maisel and Gary Cokins.  Examines how predictive business analytics can help … understand business performance based on extensive use of data, statistical and quantitative analysis, and explanatory and predictive modeling. Written for senior financial professionals  $35 272 pg.

Data Smart: Science for Insight

Data Smart: Using Data Science to Transform Information into Insight by John W. Foreman.  “Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet.”  $30 432 pages pb.

Decision Analytics using Excel

Decision Analytics: Microsoft Excel by Conrad Carlberg.  “Overwhelmed by all the Big Data now available to you?” “Using Microsoft Excel and proven decision analytics techniques, you can distill all that data into manageable sets—and use them to optimize a wide variety of business and investment decisions.” “Comes with … downloadable Excel workbooks.”  $28 288 pages pb

Marketing Analytics w. Excel

Marketing Analytics: Data-Driven Techniques with Microsoft Excel by Wayne Winston.  “Helping tech-savvy marketers and data analysts solve real-world business problems with Excel.” “shows you how to tap a simple and cost-effective tool, Microsoft Excel, to solve specific business problems using powerful analytic techniques—and achieve optimum results.”  $35 720 pg

Pivot Table Data Crunching

Excel 2013 Pivot Table Data Crunching (MrExcel Library) by Bill Jelen and Michael Alexander.  “learn how to generate complex pivot reports complete with drill-down capabilities and accompanying charts. Then, you go even further, discovering how to build a comprehensive, dynamic pivot table reporting system for any business task or function.”  $28 432 pages pb

Quant. Decision Making: Excel

Quantitative Methods for Decision Making Using Excel by Glyn Davis and Branko Pecar.  “Authors approach a range of methods, dividing them into major enterprise functions such as marketing, sales, business development, manufacturing, quality control, and finance. The authors illustrate how the methods can be applied in practice.”  $56 608 pages

Communicate with Numbers

Essentials of Business Statistics: Communicating With Numbers by Sanjiv Jaggia and Alison Kelly.  “a core statistics textbook that … bridges the gap between how statistics is taught and how practitioners think about and apply statistical methods. Throughout the text, the emphasis is on communicating with numbers rather than on number crunching.”  $160

Teaching Statistics

How to Raise a Family Using The Concepts of Statistics: A Primer on Understanding the Complex World of Statistical Models by Dr. Russell Leo Roberson.  Professors focus “too much on the mathematics..” Proposes “a new model for teaching statistics and a set of general rules governing how statistical concepts should be studied and applied.”  $24 354 pages

Understand Business Stats

Understanding Business Statistics by Ned Freed, Stacey Jones and Timothy Bergquist.  “An intuitive discussion of basic statistical principles rather than a mathematically rigorous development. They use simple examples to introduce and develop concepts and procedures.”  $99 pb

Statistics: Learn from Data

Preliminary Edition of Statistics: Learning from Data by Roxy Peck.  “Two unique chapters, one on statistical inference and another on learning from experiment data, address two common areas of confusion: choosing a particular inference method and using inference methods with experimental data.”  $76 720 pg

Advanced Statistical Methods

Understanding Advanced Statistical Methods (Chapman & Hall/CRC Texts in Statistical Science) by Peter Westfall and Kevin S. S. Henning. Teaches students “to think differently not only about math and statistics but also about general research and the scientific method.” “presents Bayesian methods before frequentist ones.” Highly Recommended!  $68 569 pages

Intro to Stats: Data Analysis

Introduction to Statistics: Fundamental Concepts and Procedures of Data Analysis by Howard M. Reid.  “redefines the way statistics can be taught and learned.” “balances development of critical thinking skills with application of those skills to contemporary statistical analysis.”  Strong recommendations.  $50 632 pg

Epidemiology: People's Health

Epidemiology and the People's Health: Theory and Context by Nancy Krieger.  “Epidemiology is often referred to as the science of public health.” “Unlike other major sciences, its theoretical foundations are rarely articulated. While the idea of epidemiologic theory may seem dry and arcane, it is at its core about explaining the people's health.” “knowledge minimizing inequitable burdens…”  $29 400 pg

Statistics Models in Epidemiology

Statistical Models in Epidemiology by David Clayton and Michael Hills.  “mathematics is deliberately kept at a manageable level.” Shows how “all statistical analysis of data is based on probability models, and once one understands the model, analysis follows easily.” Based on a highly successful course, this book explains the essential statistics for all epidemiologists.”  $47 Reprint 384 pages

Econometrics for Dummies

Econometrics For Dummies (For Dummies (Business & Personal Finance) by Roberto Pedace.  Studies “the classical linear regression model (CLRM), which is the foundation of traditional econometric analysis.” Studies “how discrete and restricted dependent variables can create problems for traditional regression analysis.” “Computer outputs from STATA”  $20 360 pgs

Intro to Econometrics

An Introduction to Econometrics: A Self-Contained Approach by Frank Westhoff.  Essentials of probability and statistics” “simple and multiple regression,.. heteroskedasticity, autocorrelation, large sample properties, instrumental variables, measurement error, omitted variables, panel data, simultaneous equations, & binary/truncated dependent variables.  $68 896 pg

Symposium: Causality & Statistics

James Robins and Thomas Richardson Single-World Intervention Graphs (SWIGS).  Unifying Directed Acyclic Graphs (DAGs) and Potential Outcomes.

Bayes: Why Bother?

Thomas Louis: Design:

• Everyone is a Bayesian in the design phase.
• All evaluations are “preposterior,” integrating over both the data (frequentist act) and the parameters (Bayesian act).
• A frequentist designs to control frequentist risk over a range of parameter values.
• A Bayesian designs to control preposterior (Bayes) risk.
• Bayesian design is effective for both Bayesian and frequentist goals and analyses.

Data Mining Applications with R

Berlin Numeracy Test

The Berlin Numeracy Test is a fast and flexible psychometric instrument, validated for use with educated samples from diverse countries (e.g., college students, computer-literate adults, physicians). Try out the Berlin Numeracy Assessment at www.riskliteracy.org/researchers/.

Trevor Butterworth, editor of STATS, contributes to the Financial Times, Forbes, and the Wall Street Journal.

ABC's Persecution Of Presidential Award-Winning Scientist Continues.

Pop a tab and pour a lie   “white-hat bias: a tendency to distort information to advance good causes”

More private liquor stores, more alcohol deaths? A.Norton

Top 50 statistics blogs of 2011.

Rebecca Goldin, STATS Director of Research, is on the Mathematics faculty at George Mason University.

Brilliant ideas from the Washington Post: Learning math is stupid! Goldin and Merrick.

High Wired: Does Addictive Internet Use Restructure the Brain?

STATS: We want people to think about the numbers behind the news.  Stats essays for 2011.

Newest 2013 Articles Posted to StatLit.org

09

Statistical Education: Steadfast or Stubborn?  Schield ASA  Audio  6up

09

Get to know variables: Critical element of statistical analysis  J Miller

09

Using Statistics to Shape Public Opinion by A Nelson  6up

09

Key Components of Numeracy Infusion Course …  Esher Wilder 2013

08

ASA President's Message: Statistical Literacy … by Ruth Carver 2012

07

David Moore Page at StatLit.org with numerous publications

07

Anne Hawkins Response to New Pedagogy …Content by Moore 1997

06

Statistical Literacy of OB-GYN Residents by Anderson et al. JGME2013

05

Display Paired Confidence Intervals using Excel by Schield 2013  1up  6up

05

Odysseys2Sense: A Startup Guide by Milo Schield 2012  6up  Audio text

05

Effects of Course on Statistical Literacy on Students  Rose Dawson

05

Causality, Change, Dichotimizing, Likert & Visual Analog Scales  Knapp

05

Bias, N versus (N-1) Re-visited, To pool or not to pool  Knapp 2013

05

Help Yourselves (& Public) Know the Truth  Vic Cohn Significance1999

04

Statistical Literacy Serves Police Officers … by Irina Soderstrom

03

Scientific reproducibility: Begley's Six Rules by Booth, Forbes 9/2012

03

New Test for Randomness: Application to Stock  Strandberg, Iglewicz

Reinventing Business Statistics

Schield presented Reinventing Business Statistics: Statistical Literacy for Managers at MBAA. 6up  “Intro Research Statistics should not be required for Business majors in Management or Marketing.” “They need Statistical Literacy for Managers: critical thinking about numbers in business.” “Of all the core courses, intro statistics is most in need of reinvention.”

Statistical Literacy using Excel

Using Excel, students (Fall 2013) simulated runs of a fair coin, clusters of rice, Law of Very Large Numbers, von Mises' Birthday problem, the Monty-Hall Three-door problem and Marilyn vos Savant's Four Envelope Problem. Modeled using Chart (linear1Y, non-linear1Y, linear2Y and Linear3factor) and Toolpak (Linear 1Y2X). Created discrete & log-normal distributions and histograms using COUNTIF. Created sampling distribution of single die.

Prediction Intervals

Prediction intervals are normally based on a mean and a standard deviation. Yet, standard deviation is seldom used in reporting stock prices.

Statistically-Significant Correlations

The formula for the distribution of a bivariate correlation is complex. See Wikipedia: Pearson Product-Moment Correlation Coefficient.  Examine the section on Inference. None of these relationships are memorable.  Statistical literacy focuses on memorable relationships.  Schield (2013) noted that rho = 2/sqrt(n) is a good estimate of the minimum correlation coefficient that is statistically significant for a given sample size. This formula is simple, memorable and slightly conservative for n > 10.

Decision Sciences Meeting

Making Statistics More Effective in Schools of Business (MSMESB) fielded over a dozen sessions at the 2013 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  lides
• M Gisela Bardossy: Mini-Cases using Baltimore Neighborhood Alliance Indicators  Slides

Significance (RSS/ASA) Vol 10 #6

• Big data and big business: Should statisticians join in?  David Walker [No] and Kaiser Fung [Yes]
• Have London’s roads become more dangerous for cyclists?  Jody Aberdein and David Spieghalter
• What happened when the legal status of cannabis was reclassified?  [Natural experiment] Ian Hamilton

Teaching Statistics:

• Using context to classify variables (pages 29–31)1 by Lawrence M. Lesser
• The danger of dichotomizing continuous variables: A visualization (pages 8–79) by Oliver Kuss
• Weighted Means Through the Looking Glass (pages 103–106) by Ruma Falk and Avital Lavie Lann

CHANCE Magazine

Using Differential Comparisons in Observational Studies by Paul Rosenbaum

“Differential comparisons are easy to do, are quite intuitive, are supported in a specific way for a specific purpose by statistical theory, and are-at worst-a harmless and transparent supplement to standard comparisons of people who look similar. Yet, differential comparisons are rarely done.”

SERJ 12:2.  Role of Context

Exploring the Role of Context in Students' Understanding of Sampling by Jacqueline Wroughton (right), McGowan, Weiss, and Cope

Analyzed “effects of confirmation bias about sampling.” Students rely “on personal experience and belief instead of principles learned in their course.” SERJ Nov 2013, 32-58.

Journal Statistics Education

An Applet for the Investigation of Simpson’s Paradox by Kady Schneiter (left) and Jürgen Symanzik (Utah State)

This applet facilitates the investigation of Simpson’s Paradox. It builds on the Baker-Kramer graphical representation for Simpson’s Paradox. This applet is used in an intro statistics class. Student responses are evaluated.  [Ed. Check out Statlets]

American Statistician

Understanding Simpson's Paradox by Judea Pearl

Simpson's paradox is often presented as a compelling demonstration of why we need statistics education. First I summarize the history of Simpson's paradox. … Next I ask what is required to declare the paradox “resolved,” and argue that modern understanding of causal inference has met those requirements. The American Statistician, Vol. 68(1): 8–13, 2014

Statistical Literacy and Statistics

• Pierce & Chick (2013) — Workplace statistical literacy for teachers: interpreting box plots. MERJ
• A. Agresti, C Franklin (2013) — Art and science of learning from data

Simpson's Paradox

Simpson's paradox in psychological science: a practical guide by Rogier A. Kievit, Willem E. Frankenhuis, Lourens J. Waldorp, and Denny Borsboom.  Frontiers in Psychology, 4, 513

ISI 2013

International Statistical Institute (ISI) held the 2013 World Statistics Conference in Hong Kong on 25-30 August.  Theme: Making Change Happen.  Detailed Program

Issues and challenges of statistical literacy in higher education by Peter Kovacs (Hungary).  “statistical literacy — several successive levels:

1. general statistical literacy, i.e. the literacy expected from common people, combined with elementary statistical language (we can read statistics)
2. the level of the users of statistics, (a competent attitude)
3. the expert professional

Two Major Themes of Analysis

Challenging the state of the art in post-introductory statistics by Tintle (right), Chance, Cobb, Rossman, Roy, Swanson & VanderStoep

“Confounding and Variation — Two substantial hindrances to drawing conclusions from data”  “the two major themes of statistical analysis”  “the concepts of confounding and variation are multivariable concepts that students should deepen their understanding of, and that models are a tool to provide that enhanced understanding.”

“We will (1) Lay out an alternative conceptual goal of a second course in Statistics—to enhance students’ understanding of confounding and variability through an approach which is not model-centered, but is instead, meaning-centered, (2) Present an outline for a curriculum that places conceptual understanding of variability and confounding at the center.”

Developing Statistical Literacy

1. Statistical literacy and multivariate thinking by James Nicholson (left), Jim Ridgway, Sean McCusker.  Abstract
2. Connected worlds: Statistical literacy in art, science, public health and social issues by Neil Lutsky.  Abstract
3. Emerging trends in data visualisation: Implications for producers of official statistics by Alan Smith

Exam results and riots: Teaching sociology via authentic contemporary data. Jim Ridgway, James Nicholson, Sean McCusker  Abstract

Visualizing Statistics

1. Seeing is believing?  Kate Richards (right), Neville Davies, G. Parkinson and D. Martignetti  “examples of poor and misleading graphs and charts … taken from the world of business and finance while others are generated from data captured from learners … in the International CensusAtSchool Project
2. On visualising our way around road blocks by Chris Wild  Abstract
3. Data visualisation and statistics from the future  Theodosia Prodromou

ISLP: Promote Statistical Literacy to Youth

1. Promoting statistics to youth through the International Statistical Literacy Project (ISLP) by Sharleen Forbes, Pedro Campos and Reija Helenius
2. Statistics under 21 by Marina Peci
3. Statistics are interesting - How do we get youngsters inspired?, K. Soinne
4. Radical statistics: Teachers and students on the highwire by Bruno de Sousa, Dulce Gomes, Regina Bispo and Elisa Duart

Statistical inference – unresolved issue

1. Informal inferential reasoning: A computer-based training environment by Joachim Engel, Tim Erickson
2. Role of statistical inference in teaching and achievement of students by Ramesh Kapadia
3. Teaching statistical inference from multiple perspectives integrating diverging schools of inference by Ödön Vancsó
4. A comparative educational study of statistical inference by Manfred Borovcnik  [Ed. Excellent historical review]

Evidence evaluation for multivariate discrete data by Colin Aitken & Erica Gold

Between media datalization and statistical literacy: China's logic by Zhongliang Zhang, Weizi Zhang

The authors argue that “without statistical literacy as a prerequisite, the room for media datalization to play a role will be greatly narrowed down; and without the existence of the media datalization, the efforts to improve statistical literacy will be tremendously limited.

IASE 2013:

The International Association for Statistics Education (IASE) held a satellite conference in Macao.  Theme: Stats Education for Progress.  ~250+ attendees.

Keynote:  Open Data, Official Statistics and Statistics Education: Threats and Opportunities for Colloration: Jim Ridgway (left), Durham Univ., UK; Mr. Alan Smith, Office for National Statistics, UK.  “There is an urgent need to rethink the statistics curriculum, and the development of statistical literacy. Statistical literacy involves a wide variety of skills and dispositions.”  Photos

“In the context of Open Data and Big Data, these include a sophisticated approach to data provenance (e. g. awareness of potential problems with metadata; plausibility of data), and to measurement (including the politics of measurement).

The technical content in curricula also needs to be reviewed. For example, the logic of the analysis of large scale multivariate data sets is rather different from the logic of drawing inferences from small samples that are then applied to populations. Key activities for analysis are: assessing effect sizes; looking for (non-linear) functional relationships; and mapping interactions. Statistical ideas that require more curriculum emphasis include: modelling functional relationships; confidence intervals; effect size; and Simpson’s paradox.”

Promoting Statistical Literacy

2.1.1  Challenge for the ISLP Project: Promotion of Statistical Literacy and User Skills Worldwide through a Co-Operation Network: Reija Helenius (right), Statistics Finland

2.3.1  Promoting Statistical Literacy among Students: Vivian W. Y. Chan, Census & Statistics Depart, Hong Kong

2.3.2  Statistical Literacy: Bringing Concepts to Life in our Diverse and Ever Changing User Communities — the Experience of the Australian Bureau of Statistics: Jonathan Palmer, Australian Bureau of Statistics

2.4.1  Another Brick in the Wall — Improving Statistical Literacy in Ireland: Steve MacFeely, Central Statistics Office, Ireland

2.4.3  Increasing Statistical Literacy through Cooperation between National Statistics Offices and Universities: A New Zealand Experience: John A. Harraway, University of Otago, New Zealand

2.5.3  iNZight into Time Series and Multiple-Response Data: Chris Wild (right), Univ. of Auckland, New Zealand

2.2.2  Integrating the Use of Official Statistics in Mainstream Curricula through Data Visualisation: James Nicholson, Durham University, UK

2.7.1  Surveys and Blaster Scatterplots at Middle School Math Nights: Adam Molnar, University of Georgia, USA

2.7.5  Statistical Significance and Practical Significance in Statistics Education: Pranesh Kumar, University of Northern British Columbia, CA

1.2.1  Enthusing Students Towards Statistical Literacy Using Transformative Learning Paradigm: Implementation and Appraisal by Shirlee Ocampo, De La Salle University, the Philippines

2.5.2  Statistical Literacy Hatching: Leticia Ruiz, National Institute of Statistics and Geography, Mexico

USCOTS 2013

United States Conference On Teaching Statistics (USCOTS) 2013 was held at Embassy Suites Hotel & Conference Center Raleigh-Durham (Research Triangle), North Carolina on May 16th – 18th.  Theme: Making Change Happen.

Changing Times

Changing Times call for Changing Stats (1up Slides) by Danny Kaplan: Causation is often the issue. But … Confounding is common, Adjustment provides insight if not proof.” Adjustment “is very common in the literature. We should change: (1) Prepare students for technical computing; (2) Mathematics should be about multiple variables; (3) Make modeling central.”

Opening Session: Horton, Stangl and Gould

Nicholas Horton: Helping Students grasp the true promise of statistics. What students need to know: Confounding!  Change: Rethink datasets that motivate our courses; Move from k = 2 to at least k = 3; Communicate the excitement of statistics (or at least give a glimpse…)

Darlene Stangl: Time for a paradigm Change: Why and How to Teach Students to be Bayesians.  Best way to decide upon action is setting up a decision table that reflects the utility of alternative actions. Bayesian thinking demands coherency, via explicitly and transparently laying out our decision table, adjusting the decision table to the context of the problem at hand, and declaring openly to others the probabilities we use in reaching a decision. This is why we must teach undergraduates to think as Bayesians.

Rob Gould: 5 epiphanies that lead me to change (in no particular order).

1. It is my fault if students didn't learn.
2. Clickers.  Make clicker questions that turn lectures into discussions.
3. Fathom.  Everyone can (and should) analyze data.  Teaching statistical literacy means teaching data analysis
4. Creation of a major
5. Statistics is important.

Closing Session: George Cobb

Conclusions:

1. TYRANNY OF THE COMPUTABLE: How we think, and what we teach, are shaped by what we can and cannot compute.
2. THE POWER OF SIMULATION: Simulation reduces computing areas and probabilities to counting # Yes / # Reps.
3. FISHER’S VISION: Fisher wanted to base p-values on randomization, but he didn’t have the computing power. We do.
4. BAYESIAN INTERVALS: Only Bayesian intervals condition on all the data, and only on the data we actually observed.
5. SIMULATION FREES US TO TEACH WHAT REALLY MATTERS: It’s not just p-values and Bayesian posteriors. We need more time on what Nick Horton and Danny Kaplan talked about yesterday.
6. THERE IS NO STATISTICAL GRAND THEORY OF EVERYTHING: We need both p-values for model choosing (Does x have a detectable effect?) AND Bayesian intervals for estimation (once we have a tentative model).

Statistical Literacy 2013

Milo Schield organized and chaired the 16th topic-contributed session on Statistical Literacy with 50 attendees at the JSM in Montreal, Ontario. Unfortunately only 14 submitted reviews (15 required for judging), so none of our papers qualified for best-speaker award. Schield's paper ranked #4 out of 35.

Get to Know Your Variables

Jane Miller (Rutgers) presented Getting to know your variables: A critical element of a statistical analysis.  “Because concepts, context, and study design all affect the valid range and interpretation of … those variables, it is important that students … get to know each of their variables before analyzing their data.”  6up  1up  Audio

Relevance of Rhetoric

Joel Best presented The Relevance of Rhetoric to Statistical Literacy. Best presents quantitative arguments advanced by conservatives (healthcare) and by liberals (welfare) that sound plausible. Best finds a common weakness in both. He argues that educators need to focus more on quantitative rhetoric — how statistics are used — or misused — in everyday arguments.

Challenging Statistical Claims

Rose Martinez-Dawson (Clemson) presented Challenging Statistical Claims in the Media Course and Gender Effects. Goal: “Evaluate students’ questions (challenges) concerning statistics encountered in everyday life and how these challenges differed before/after taking a course focused on statistical literacy.  6up  1up  Audio

Stat Ed: Steadfast or Stubborn?

Milo Schield (Augsburg College) presented Statistical Education: Steadfast or Stubborn. He argued that statistical education had resisted calls for change from its leaders over the past 60 years and was closer to a math-stat course than to a context-based statistics course. He presented ways in which context could be shown to influence statistical significance.  6up  1up.  Audio

Numeracy Infusion Components

Ester Wilder (Lehman) presented A Numeracy Infusion Course for Higher Education … to Train Faculty: 1) QR and Making Numbers Meaningful; 2) QR Learning Outcomes; 3) The Brain, Cognition and QR; 4) QR and Writing; 5) Discovery Methods; 6) Representations of Data; 7) QR Assessment; and 8) QR Stereotypes & Culture.  6up.

Published Papers

Here are statistics on those papers published in the ASA-JSM Proceedings:

• Five papers including “confound” in their title or abstract (two of these are Schield and Pearl).
• Eight papers included “statistical literacy” in their title or abstract (one of these is Schield).
• 52 included the phrase “caus” (e.g., cause, causal, etc.)

Mathematics of Causal Inference

This paper by Judea Pearl “reviews concepts, principles and tools that have led to a coherent mathematical theory of causation based on structural models. The theory provides solutions to a number of problems in causal inference, including questions of confounding control, policy analysis, mediation, missing data and the integration of data from diverse studies.”

Fusion in Big Data

Fusion and causal analysis in big marketing data sets by Igor Mandel (Telmar Group). “Purpose of ascription (fusion) is to merge information of two datasets into one, in a such a way, that external criteria are satisfied.” “Individual and statistical causes … could be looked at under different angles, and mixing these is, maybe, the main source of confusion in literature.”  [Editor. An excellent paper]

Visualize Economic Indicators

Dynamic Visualization of Economic Indicators by Katherine (Jenny) Thompson (US Census Bureau). This report presents the ongoing efforts at the U.S. Census Bureau to develop and implement a standard set of data visualization tools for usage with its monthly and quarterly economic indicators.

Assumptions and Benford's Law

Reality Checks for a Distributional Assumption: The Case of “Benford’s Law” by William Goodman. Demonstrates that while Benford’s-like patterns are indeed common, Benford's per se is not a unique and universal template for all cases of interest to fraud investigators. “Reminds us of how, in general, distributional assumptions can sometimes be overlooked or fail to be critically questioned.”

Uses of Convenience Samples

Assessing Limitations and Uses of Convenience Samples: A Guide for Graduate Students by Kriska et. al.  “This poster takes the view that all samples of human participants are convenience samples to some degree.” “Because some convenience samples may be better than others, this poster session will examine factors and issues in sample selection.”

As of 2013

Advanced Search (12/2013):

• Subject = Science-Math, Keyword = Statistics,  Language = English  Published before Jan 2014  Sort-by = Best Selling
• Results appear with Sort = Relevance
• Excludes Kindle editions, textbooks, free Creative Commons (CK-12) books, required “books” (My MathLab) and non-books.

1. Outliers: The Story of Success by Malcolm Gladwell
2. Freakonomics Rev Ed. by Levitt and Dubner 2010
3. Big Data: A Revolution … by Mayer-Schönberger & Cukier Mar 2013
4. The Visual Display of Quantitative Information, 2nd ed. by Tufte 2001.
5. Data Science for Business by Provost and Fawcett Jul 2013
6. Cartoon Guide to Statistics by Larry Gonick, Woollcott Smith.
7. World Almanac and Book of Facts 2014 by Sarah Janssen 2013
8. Naked Statistics: Stripping Dread from Data by Wheelan 2012
9. Research Design: Qualitative, Quantitative & Mixed by Creswell 2008
10. Fooled by Randomness: The Hidden Role of Chance by Nassim Taleb.
11. Doing Data Science: Straight Talk from Frontline: O'Neil & Schutt 2013
12. How to Lie with Statistics by Darrell Huff and Irving Geis 1993
13. Lean Analytics: Use Data, Build Better Startup: Croll & Boskovitz 2013
14. Against the Gods: The Remarkable Story of Risk by Bernstein 1998
15. Design and Analysis of Experiments by Montgomery 2012
16. Experimental and Quasi-Experimental Designs for Generalized Causal Inference by William Shadish, Thomas Cook and Donald Campbell 2001
17. The Drunkard's Walk: How Randomness Rules Our Lives: Mlodinow 2009
18. Now You See It: Visualization for Quantitative Analysis: Few 2009
19. Qualitative Research & Evaluation Methods by Patton 2001
20. Intuitive Biostatistics: AGuide to Statistical Thinking: Motulsky 2010
21. Pattern Recognition and Machine Learning by Bishop 2007
22. How to Prove It: A Structured Approach by Daniel J. Velleman 2006
23. Bayes' Rule: A Tutorial Introduction by James V Stone Jun 2013
24. Cartoon Introduction to Statistics by Klein and Dabney Jul 2013
25. Think Bayes by Allen B. Downey Sep 2013

Published during 2013

Advanced Search:

• Subject: Science/Math, Keyword: Statistics, Published during 2013, Sort: New and Popular
• Exclude Kindle editions, textbooks and non-books: game cards, calendars, Cliff notes, coloring books, GRE/SAT/AP workbooks, logic puzzles, Mathlab access.

1. Big Data: A Revolution … by Mayer-Schönberger & Cukier
2. Data Science for Business by Provost and Fawcett
3. Doing Data Science: Straight Talk from Frontline: O'Neil & Schutt
4. Applied Predictive Modeling: Max Kyhn and Kjell Johnson
5. Bayes' Rule: A Tutorial Introduction by James V Stone
6. Modelling Techniques with Predictive Analytics by Thomas Miller
7. Cartoon Introduction to Statistics by Grady Klein and Alan Dabney
8. Lean Analytics: Build Startup Faster by Alistair Croil and B. Yoskovitz
9. Intro Mediation, Moderation, and Conditional Process Analysis: Hayes
10. Analyzing Baseball Data with R by Max Marchi and Jim Albert
11. Bad Pharma: How Drug Companies Mislead and Harm by Ben Goldacre
12. Think Bayes by Allen B. Downey
13. Keeping up with the Quants by Thomas Davenport and Jinjo Kim
14. Data Mining Applications with R by Yanchang Zhao and Yonghua Cen
15. Sports Analytics: Guide for … Decision Makers by Alamar and Oliver
16. Stats and Curiosities from Harvard Business Review by HBR
17. Poor Numbers: Mislead by African Development Stats by Jerven
18. From STEM to STEAM: Using Brain-Compatible Strategies to Integrate the Arts by David Sousa and Thomas Pilecki
19. Decision Analytics: MS Excel by Conrad Carlberg
20. Analyzing Social Networks by Borgatti, Everett and Johnson
21. Will you be alive in 20 years — Probability by Paul Nahin
22. Multivariate Time Series Analysis with R by Ruey Tsay
23. Biostatistics for Dummies by Pezzuilo
24. Who's bigger: Where historical figures really rank by Skiena and Ward
25. High-yield Biostatistics, epidemiology and Public Health by Glaser

PDFs downloaded from StatLit.org in 2013

Total downloads: 265,000 in 2013; 246,000 in 2012; 198,000 in 2011; 207,000 in 2010; 184,000 in 2009; 106,000 in 2008. Counts in parenthesis are (2013; 2012; 2011; 2010; 2009; 2008). As of Dec. 2013, the StatLit website hosted 1,114 pdfs: 787 papers and 327 slides.

1. Percentage Graphs in USA Today. Milo Schield 2006 ASA Proceedings. (7771; 17,819; 19,114; 11,179; 13,253; 14,247; 8809) Total: 93,216.
2. Statistical Literacy: Uses & Abuses of Numbers by Andrew Nelson 6up  (4,912)
3. Presenting Confounding Graphically Using Standardization by Milo Schield. 2006 STATS magazine. (3709 [11]; 4646; 1289; 2084; 1985; 1616) Total: 15,329
4. Statistical Literacy: A New Mission for Data Producers by Milo Schield. 2011 SJIAOS (3104 [8]; 2815 [10]; 1723) Total: 7,642
5. Univ. Texas San Antonio: Quantitative Scholarship — Final Draft  Press release 2009  (1896 [4])
6. Statistics for Political Science Majors.  Gary Klass 2004 ASA (1817; 1416[10]; 1389[10]; 596[6]; 765; 215)
7. Interpreting the substantive significance of multivariate regression coefficients. Jane Miller 2008 ASA (1,630 [9]; 3,118; 1625[11]; 2094; 1412)
8. Interpreting the Cumulative Frequency Distribution of Socio-Economic Data. Othmar Winkler 2009 ASA (1,515 [11]; 822[7])
9. Random Sampling versus Representative Samples by Milo Schield. 1994 ASA. (1,328) [This was the first paper given by Schield at JSM. In the Q&A following his talk, the first respondent said “I have authored many papers in statistics, and I maintain that you, Sir, are undermining the theoretical foundations of our discipline.” The next respondent said “This is good paper; we need more of this kind of thinking.”]
10. Assessing Students’ Attitudes: The Good, the Bad, and the Ugly by Anne Millar and Candace Schau 2010 ASA. (1,024 [6])
11. Coincidence in Runs and Clusters. Milo Schield 2012 MAA (915 [5]; 2,466[9])

12. Making Statistics Memorable: New Mnemonics and Motivations by Larry Lesser. ASA 2011. (900 [8])
13. Exploring Simpson's Paradox. Larry Lesser (Univ. Texas, El Paso) NCTM 2001 (813 [6]; 1,686[9]; 1143[9]; 2043[11]; 2844; 913)
14. Statistical Literacy Curriculum Design, 2004 Milo Schield IASE (760 [6]; 457[2])
15. Social Mathematics in US Civics Curriculum. James Mauch dissertation 2005 (759 [5]; 801[4]; 792[5]; 858[7]; 442; 470)
16. Statistical Literacy and Chance by Milo Schield. 2005 ASA 6up (747[5])
17. Toward a Clearer Definition of Confounding by Clarice Weinberg. 1993 American Journal of Epidemiology (676 [5])
18. Statistical literacy in adult college students: Table of Contents by Barbara Wade 2009 PhD Thesis. (672 [4])
19. How to spot spin and inappropriate use of statistics by Paul Bolton 2009 UK House of Commons Library. (656 [6])
20. Learning Statistics through Playing Cards by Thomas R. Knapp, 2012. (571 [5]).
21. The Cult of Statistical Significance by Stephen Ziliak and Deirdre McCloskey 2009 ASA 6up 4up (520 [5]; 890[8]; 3160; 3972; 999)
22. Ambiguity Intolerance: An Impediment to Inferential Reasoning?. Robert Carver 2006 ASA (1,370 [11]; 1220; 624[5]; 797)
23. Pop-Stats Books and Statistical Education by Kaiser Fung, ASA 2011. 1up (501[3]).
24. Assessing Validity and Reliability of Likert and Visual Analog(-ue) Scales by Thomas R. Knapp, 2013. ** New this year. {499 [4]).
25. It May Be a Great Day for Baseball, but Is It a Great Day for a Knuckleball?. Robert H. Carver 2011 ASA (444[3]; 472[3]) 6up
26. Three Paradoxes. Howard Wainer and Lisa Brown, Nat. Board of Med. Examiners. Draft American Statistician 2004 (336 [3]; 716[6]; 913[9]; 1084[10]; 315; 750)
27. 32 Principles of Data Interpretation by Gerald Bracey 2006. Grouped (322 [1]).
28. Accuracy and Apparent Accuracy in Medical Testing by Boersma and Willard, MAA 2009. 6up only. (320 [2])

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).  It excludes pdfs that are required for courses (Excel step-by-step instructions). 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 2013

(####; ####; ###; ###): page views 2013, 2012; 2011; 2010; 2009; 2008.

Note the 61% increase in page views for Index over 2012.

1. Index (47,674; 29,554; 28,157, 23,159; 15,729; 10,423): Home
2. Standardizing (9809; 6633; 5176; 3265; 2434; 1718): Excel displays
3. Joel Best (3451; 4617; 5036; 4794; 3481; 3118): Author
4. Howard Wainer (3396; 4296; 3893; 2778; 2127; 1966): Author
5. StatLit Papers (2914; 3073; 4203; 3131; 2837; 2444)
6. StatLit News 2012 (2891; 1297[7])
7. StatLit News 2010 (2836; 2693; 2963)
8. Adult Numeracy (2784; 4070; 4998, 5007; 2467; 1987)
9. StatLit News 2011 (2562; 3023)
10. StatLit News 2008 (2501; 2698; 2975; 3333; 2634)
11. StatLit News 2009 (2269; 2797; 3228; 4869)
12. Q/L Textbooks (1868 [10]; 2233; 3159; 2741; 2484; 2387): QL3
13. Gerd Gigerenzer (1713*; 2283; 2567; 1993*; 1415; 1503): Author
14. Q/L Activities (1605*; 1886; 2106; 1725*; 1278; 1378): QL2
15. StatLit News 2007 (1527*; 1940; 2127; 2552; 1498; 1928)
16. Q/L Books (1522*; 1884; 2305; 1418; 1459): QLit (No textbooks)
17. Gerald Bracey (1487; 1923; 2374; 2655; 2669; 2,035): Author
18. Schield (1410* [9]): Author and webmaster of StatLit.org
19. Blastland (1331* [9]): Author of “The Tiger that Isn't”
20. StatLit News 2004 (808 [6]; 1268[9]; 1738; 1929; 1191; 1183)

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

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.