David S. Moore is Shanti S. Gupta Distinguished
Professor of Statistics, Emeritus, at Purdue University and was 1998
president of the American Statistical Association. He received his A.B. from
Princeton and his Ph.D. from Cornell, both in mathematics. He has written
many research papers in statistical theory and served on the editorial
boards of several major journals. Professor Moore is an elected fellow of
the American Statistical Association and of the Institute of Mathematical
Statistics and an elected member of the International Statistical Institute.
He has served as program director for statistics and probability at the
National Science Foundation. In recent years, Professor Moore has devoted
his attention to the teaching of statistics. He was the content developer
for the Annenberg/Corporation for Public Broadcasting college-level
telecourse Against All Odds: Inside Statistics and for the series of video
modules Statistics: Decisions through Data.
David Sheldon Moore should not be confused with a David S. Moore: Professor of Developmental Psychology at Pfitzer College and Director, Claremont Infant Study Center
Interview with David Moore by Allan Rossman and E. Jacquelin Dietz. On statistics education for undergraduates (majors or not) and perhaps secondary school students: "little of real substance has changed in the past 20 years, the 1997 advent of AP Statistics being the most significant exception." Journal of Statistics Education, Volume 21 , Number 2 (2013 ).
A Generation of Statistics Education: An Interview with Frederick Mosteller by David S. Moore (JSE, 1993).
Per David Moore: "Please be aware that my texts are now other hands, all except Basic Practice and Essential Statistics for some time, even though they continue to bear my name. In one case (Exploring the Practice of Statistics) I had no involvement in preparing the text. Please direct text questions to the current authors."
8th ed. 7th ed. 6th ed. 5th ed. 3rd ed.
Preface (3rd edition): This is a statistics book for readers interested in ideas rather than technique. It presents, in a non-technical form, the most important statistical concepts as they are applied in public policy, the human sciences, and everyday life. It is designed to give non-mathematical readers critical insight into the uses and misuses of numbers and quantitative arguments, which are increasingly prevalent in fields ranging from sociology to medicine to literary analysis. The goal is not to train statisticians, but to present statistics as a useful tool for clear thinking in personal and professional life. The third edition has been revised and updated, placing more emphasis on giving students hands-on experience with data. Chapters 4 and 5 have been reorganized into a more logical arrangement. Many new examples and exercises have been added. --This text refers to an alternate Paperback edition.
STATISTICS EDUCATION ARTICLES by David Moore:
The Craft of Teaching. MAA FOCUS 15 (1995) Number 2, 5-8.
Statistics Education Fin de Siècle.
Moore, Cobb, Garfield & Meeker.
TR95-10 The American Statistician 49 (1995), 250-260.
Multimedia for Teaching Statistics: Promises and Pitfalls. Velleman and Moore.
TR95-13 The American Statistician 50(1996) 217-225
Bayes for Beginners? Some Reasons to Hesitate.
TR93-33. The American Statistician, 51 (1997), 254-261 and
Bayes for Beginners? Some Pedagogical Questions. Advances in
Statistical Decision Theory, Birkhäuser, Boston, 1997, 3-17.
New pedagogy and new content: the case of statistics.
TR96-37. International Statistical Review, 65, 123-165.
Statistics, and Teaching". D. Moore and G. Cobb. American
Mathematical Monthly, 104 (1997), 801-823.
"Statistics among the liberal arts" American Statistical
Association 1998 Presidential Address, JASA, pp. 1253-1259
1999: What Shall We Teach Beginners?. Invited discussion of a paper by Wild and Pfannkuch. ISR 67 (1999), 250-252. Copy
Teaching Beginners as a Mirror of the Discipline.
Australian and New Zealand Journal of Statistics 41 (1999), 135-137.
Statistics and Mathematics: Tension and Cooperation. Moore & Cobb.
American Mathematical Monthly, 2000, pp. 615-630.
Undergraduate Programs and the Future of Academic Statistics.
The American Statistician, 2001, pp. 1-6.
Preparing Graduate Students to Teach Statistics: Introduction. The
American Statistician, 2005, pp 1-3.
STAT-ED ABSTRACTS AND SLIDES-ONLY:
1997: Statistical Literacy and Statistical Competence in the 21st Century. Slides [Ed, No definitions]
1998: Statistical Literacy and Statistical Competence in the 21st Century. MSMESB Univ. Iowa Abstract-only. "Educated people face a new environment at century's end: work is becoming intellectualized, formal higher education more common, technology almost universal, and information (as well as mis- and dis-information) a flood. In this setting, what is statistical literacy , what every educated person should know? What is statistical competence, roughly the content of a first course for those who must deal with data in their work? One might define competence as what we hope a business statistics student will retain five years later."
2001: Statistical Literacy and Statistical Competence in the New Century. IASE
Copy [Ed. No definitions]
In some of these slides, Professor Moore presented this challenge: "If the rocket goes up, I don't care where it comes down" In 2013, when asked for an explanation, he said "The "If the rocket ..." line is from the classic Tom Lehrer song "Werner von Braun." In that context it referred to a technical expert being satisfied with technical success without regard for real world consequences or moral issues."
Professor Moore also presented this challenge: "Does statistics have a core?". When asked for an explanation in 2013, he replied, "As you might guess, I have no idea what I said 12 years ago to accompany that line in the projected outline. Probably something like statistics in practice is more than technique."
TECHNICAL ARTICLES by David Moore:
1968: Asymptotically nearly efficient estimators of multivariate location parameters (now in reprint form). TR68-10. Published in Annals of Mathematical Statistics, Vol. 40, pp. 1809-1823, 1969.
1968: Uniform consistency of some estimates of a density function. [TR68-99] E. G. Henrichon, D. S. Moore. Published in Annals of Mathematical Statistics, Vol. 40, pp. 1499-1502, 1969.
1969: Asymptotically nearly efficient procedures for bivariate location parameters. [TR69-99] Annals of the Institute of Statistical Mathematics, Vol. 22, pp. 41-49, 1970.
1969: A chi-square statistic with random cell boundaries. [TR-206] Published in Annals of Mathematical Statistics, Vol. 42, pp. 147--156, 1971.
1986: David S. Moore, Tests of chi-squared type, in Ralph B. D'Agostino and Michael A. Stephens, (eds.), Goodness-of-Fit Techniques, Marcel Dekker, New York, 1986, pp. 63-95.
1970: On multivariate chi-square statistics with random cell boundaries. [TR-236]
1970: Asymptotically efficient estimation by local-parameter approximations. Published in Annals of the Institute of Statistical Mathematics, Vol. 24, No. 2, pp. 299-308, 1972.
1972: A note on Srinivasan's goodness of fit test. [TR-293] Published in Biometrika, Vol. 60, pp. 209-211, 1973.
1975: A unified large-sample theory for chi-square statistics for tests of fit. D. S. Moore and M. C. Spruill. Published in The Annals of Statistics, Vol. 3, No. 3, pp. 599-616, 1975.
1976: Large sample comparison of tests and empirical Bayes procedures. J. C. Kiefer and D. S. Moore. Published in On the History of Statistics and Probability, Editor D.B. Owen, Marcel Dekker, Inc., 1976, pp. 349- 365.
Statistical Decision Theory and Related Topics, Editors. S.S. Gupta and D.S. Moore, New York: Academic Press, pp. 139-155.
1975: Variance comparison for unbiased estimators of probabilities of correct classifications. D. S. Moore, S. J. Whitsitt, D. A. Landgrebe. [TR-401] Published in IEEE Transactions on Information Theory, Vol. 22, pp. 102-105, 1976.
1975: Generalized inverse, Wald's method, and the construction of chi-square tests of fit. [TR-405] Published in Journal of the American Statistical Association, Vol. 72, pp. 131-137, 1977.
1977: Consistency properties of nearest neighbor density function estimators. D. S. Moore and J. Yackel. Published in The Annals of Statistics, Vol. 5, No. 1, pp. 143-154, 1977.
1977: Large sample properties of nearest neighbor density function estimators. D. S. Moore and J. W. Yackel. Published in Statistical Decision Theory and Related Topics, II, Editors S.S. Gupta and D.S. Moore, pp. 269-279, Academic Press, 1977.
1976: Recent developments in chi-square tests for goodness of fit. [TR-459]
1978: Chi-square tests. [TR-469] Published in Studies in Statistics, Editor R. Hogg, pp. 66-106, 1978.
1977: Chi-square tests of fit for type II censored data. D. P. Mihalko, D. S. Moore. [TR-505] Published in Annals of Statistics, Vol. 8, pp. 645-644, 1980
1978: Chi-square tests for multivariate normality with application to common stock prices. D. S. Moore and J. B. Stubblebine. [TR78-17] Published in Communications in Statistics, Vol. A10, pp. 713-738, 1980.
1980: The effect of dependence on chi-square tests of fit. [TR80-21] Published in Annals of Statistics, Vol. 10, pp. 1163-1171, 1982.
1982: The effect of dependence on chi-squared and empiric distribution tests of fit. L. J. Gleser, D. S. Moore. [TR82-21] Published in Annals of Statistics, Vol. 11, pp. 1100-1108, 1983.
1983: Measures of Lack of Fit From Tests of Chi-Squared Type. [TR83-12] Published in Journal of Statistical Planning and Inference, Vol. 8, pp. 151-166, 1984.
1983: Chi-Squared Tests of Fit - A Survey for Users. [TR83-53] Published in Goodness of Fit Techniques, Editors R. D'Agostini and M. A. Stephens, pp. 63--95, 1986.
1984: The effect of positive dependence on chi-squared tests for categorical data. L. J. Gleser and D. S. Moore. [TR84-20] Published in Journal of the Royal Statistical Society, Vol. B47, pp. 459--465, 1985.
1984: Positive Dependence in Markov Chains. L. J. Gleser and D. S. Moore. [TR84-22] Published in Linear Algebra and Applications, Vol. 70, pp. 131-146, 1985.
1986: Computers in statistical research. Statistical Science 1 (1986) 419-437 (with W. F. Eddy et al.).
1989: Power approximations to multinomial tests of fit. Journal of the American Statistical Association 84 (1989) 130-141 (with J. Oosterhoff et al.).
1989: Asymptotic error bounds for power approximations to multinomial tests of fit. Contributions to Probability and Statistics: Essays in Honor of Ingram Olkin. Springer, 1989, 385-402. (with J. Oosterhoff et al.).
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