Milo Schield

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
E-mail: schield@augsburg.edu;
 

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.

 

Statistical Literacy should focus
… 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

more on modeling the association between variables than on the tests of statistical significance
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.

 

Publications on Statistical Literacy:

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: Difficulties in Describing and Comparing Rates and Percentages 2000 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:

·        Confounder-Resistance and Confounder Intervals for a Binary Confounder, 2004 JSM ASA

·        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

·         Correlation, Determination and Causation in Introductory Statistics, 1995 JSM

·         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

·         Proposed Survey of Business Statistics Teachers.  MSMESB Conference 6/2002. 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

Miscellaneous:

·         Statistical Literacy Survey [PDF]      

·         Questionnaire: Topics in a Statistical Literacy course [PDF]      

·         US Census Bureau Proposal

·         Interesting books on Statistics

·         Interesting books on Critical Thinking

·         Curriculum Vitae

·         Three Key Problems in the Humanities 2004 New Directions in the Humanities Prato Italy.

 

Professional Goals:

·         Giving talks, writing essays and networking on statistical literacy.

Personal/Family:

·         The Fred and Emma Schield Family History (including the Schield Bantam Company).

Source: www.augsburg.edu/ppages/~schield/index.htm (Not *.html)
The papers in PDF format are viewable with Adobe Acrobat Reader.
Disclaimer: Personal Web pages published by Augsburg College students, faculty and staff reflect their own thoughts, interests and activities.  They do not implicitly or explicitly represent official information about Augsburg College or its positions and policies.  Personal page publishers assume responsibility and liability for the content of their documents.  Please address all comments and other feedback to the publisher of the personal pages. For further assistance, contact webmaster@augsburg.edu