Statistical literacy is critical thinking about statistics in arguments.
Director of the W. M. Keck Statistical Literacy Project
US Representative of the International Statistical Literacy Project
Member of the International Statistical Institute
President of the Twin-Cities chapter of the American Statistical Association
Webmaster of www.StatLit.org
Professor, Dept. of Business
Administration, Augsburg College, Minneapolis
Viewpoint on Education:
Every student should work at mastering grade-appropriate skills in critical thinking. Critical thinking focuses on identifying and evaluating arguments supporting the truth of disputable claims. Critical thinking focuses on both deductive and inductive arguments. In deductive arguments, the focus is on verifying their validity; in inductive arguments the focus in on evaluating their strength. Inductive arguments focus heavily on explanations, the distinction between reasons and causes, and the distinction between association and causation.
Every student should work at mastering grade-appropriate skills in statistical literacy. Statistical literacy is critical thinking about statistics as evidence for inferences. All college graduates should be statistically literate -- not necessarily about the binomial distribution, probability, sampling distributions and p-values but about those more-informal arguments that use statistics as evidence. Statistical literacy should give students the ability to describe, compare and interpret statistics contained in tables and graphs. Statistical literacy should give students the ability to evaluate the strength of statistics as evidence in arguments about causation. Students should be able to read and critically evaluate statistically-based arguments involving public policy such as The Bell Curve (Herrnstein and Murray), More Guns -- Less Crime (Lott), Population and Development (Simon), The Tyranny of Numbers (Eberstadt), Economics and Politics of Race (Sowell) and Criminal Justice (Bidinotto) as well as the many health related books involving statistics.
… more on descriptive statistics and modeling than on statistical inference.
… more on reading and interpreting tables and graphs than on sampling distributions.
… more on observational studies than on experiments.
… more on confounding factors and bias than on chance
on modeling the association between variables than on the tests of
… more on inductive inference than on deductive inference.
… more on Bayesian reasoning than on classical frequentist reasoning.
… more on the quality of statistical arguments about social policy than on the fit of data to theory
… more on the support provided by a statistic if true than on the truth of that statistic.
Statistical Literacy: An overview:
· Statistical Literacy and Liberal Education at Augsburg, 2004 Peer Review AACU
· Statistical Literacy: Thinking Critically About Statistics, 1999 APDU Of Significance
· Statistical Literacy and Mathematical Thinking, 2000 ICME-9 Tokyo
· Statistical Literacy and Evidential Statistics, 1998 JSM ASA
· Three Kinds of Statistical Literacy, 2002 ICOTS-6 Durban, South Africa
Statistical Literacy Data Analysis
· Frequency of Simpson's Paradox in NAEP Data, AERA Co-authored with James Terwilliger
Statistical Literacy Curriculum:
· Statistical Literacy Curriculum Design, 2004 IASE Roundtable, Lund Sweden
· Three Graphs for Statistical Literacy, 2004 ICME-10, Copenhagen Denmark
Statistical Literacy and Descriptive Statistics:
· Describing Rates and Percentages in Tables, 2001 Business of Communications Conference
· Statistical Literacy, Simpson's Paradox and Minimum Effect Size, 1999 JSM ASA
· Statistical Literacy: Reading Tables of Rates and Percentages, 2001 JSM ASA
· Common Errors in Forming Arithmetic Comparisons, 1999 APDU Of Significance
Algebra of Association and Confounding:
· Epidemiology and Statistics: Algebraic Association in 2x2 Tables, 2002 JSM ASA
· Confounder-Induced Spuriousity and Reversal, 2003 JSM ASA
Statistical Literacy and Inferential Statistics:
· Using Bayesian Strength of Belief to Teach Classical Statistics, 1998 ICOTS-5, Singapore
· Interpreting Statistical Confidence, 1997 JSM American Statistical Association
· Using Bayesian Inference in Classical Hypothesis Testing, 1996 JSM ASA
· Random Sampling versus Representative Samples, 1994 JSM ASA
Power Point Slides of Talks
· Epidemiology and Statistics: Algebraic Associations in 2x2 Tables. 2002 JSM ASA. Six-up
· Reading Tables of Rates and Percentages. Royal Statistical Society 10/2001.
· The Grenada Conjectures: The Future of Statistical Education Univ. of Grenada 1/2001.
· Reading Tables. APDU Conference, October, 1999. Six-up
· Statistical Literacy Survey [PDF]
· Three Key Problems in the Humanities 2004 New Directions in the Humanities Prato Italy.
· Giving talks, writing essays and networking on statistical literacy.
Source: www.augsburg.edu/ppages/~schield/index.htm (Not *.html)
The papers in PDF format are viewable with Adobe Acrobat Reader.
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