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Statistics Curricula, March Madness Featured in May Issue

1 June 2010 2,496 views One Comment
John Stufken, Editor, The American Statistician

    Book Reviews
    Applied Spatial Data Analysis with R
    Roger S. Bivand, Edzer J. Pebesma, and Virgilio Gómez-Rubio

      The Art of Conjecturing, together with Letter to a Friend on Sets in Court Tennis
      Jacob Bernoulli, translated by Edith Dudley Sylla

        Bioconductor Case Studies
        Florian Hahne, Wolfgang Huber, Robert Gentleman, and Seth Falcon

          Business Statistics
          Norean R. Sharpe, Richard D. De Veaux, and Paul F. Velleman

            Dynamical Processes on Complex Networks
            Alain Barrat, Marc Barthélemy, and Alessandro Vespignani

              Graph Theory: A Problem Oriented Approach
              Daniel A. Marcus

                Introduction to Probability and Statistics for Science, Engineering, and Finance
                Walter A. Rosenkrantz

                  The Monty Hall Problem: The Remarkable Story of Math’s Most Contentious Brain Teaser
                  Jason Rosenhouse

                    New Drug Development: Design, Methodology, and Analysis
                    J. Rick Turner

                      SAS for Data Analysis: Intermediate Statistical Methods
                      Mervyn G. Marasinghe and William J. Kennedy

                        The Unfinished Game: Pascal, Fermat, and the Seventeenth-Century Letter That Made the World Modern
                        Keith Devlin

                          Wavelet Methods in Statistics with R
                          G. P. Nason

                            Applied Survival Analysis: Regression Modeling of Time-to-Event Data (2nd ed.)
                            David W. Hosmer, Stanley Lemeshow, and Susanne May

                              The Little SAS Book: A Primer (4th ed.)
                              Lora D. Delwiche and Susan J. Slaughter

                                Statistics: Informed Decisions Using Data (3rd ed.)
                                Michael Sullivan III

                                The featured article in the May issue is “Computing in the Statistics Curricula,” by Deborah Nolan and Duncan Temple Lang. The authors argue that this is an opportune time to make significant changes in statistics curricula and focus their attention on the integration of computational topics with the teaching of modern statistical methods. Nolan and Lang advocate that computing must be central to the statistics curricula at both the undergraduate and graduate levels and that computational topics must be integrated into traditional statistics courses. The article presents a broad set of computational topics with ideas on how to teach them.

                                In the General section, Paul Fearnhead and Benjamin M. Taylor extend the madness of the NCAA basketball season in “Calculating Strength of Schedule and Choosing Teams for March Madness.” The authors propose a method to select teams for the NCAA tournament based on their win-loss records after accounting for the different opponents they have played.

                                David H. Annis, Peter C. Kiessler, Robert Lund, and Tara L. Steuber propose a symmetrized moment estimator for estimation of the one-step-ahead transition probabilities in a reversible Markov chain on a countable state space in “Estimation in Reversible Markov Chains.”

                                Devan V. Mehrotra, Xiaomin Lu, and Xiaoming Li propose and study two alternatives to the van Elteren test, which uses
                                within-stratum ranks, for comparing two treatments in a stratified experiment.

                                In “Three Examples of Accurate Likelihood Inference,” C. Lozada-Can and A. C. Davison demonstrate through illuminating examples that, computationally, it can be relatively straightforward to use higher-order corrections for improving standard likelihood inference.

                                In the final contribution to this section, Gunnar Taraldsen and Bo Henry Lindqvist present an elementary introduction to a theoretical framework for statistics that includes improper priors, considering both Bayesian and non-Bayesian models.

                                The Statistical Practice section opens with “A Note on Bayesian Inference After Multiple Imputation,” by Xiang Zhou and Jerome P. Reiter, who consider Bayesian inference on multiply imputed data sets in settings in which posterior distributions of the parameters of interest are not approximately Gaussian. Nicholas T. Longford follows with “Bayesian Decision Making About Small Binomial Rates with Uncertainty About the Prior.”

                                In “Is the t Confidence Interval: ± t‹(n − 1)s/ Optimal?”, Yijun Zuo proposes a new procedure for constructing a confidence interval for an unknown mean parameter that can outperform not only the classical interval in the title but also bootstrap confidence intervals.

                                In the History Corner section, Michael Friendly, Pedro Valero-Mora, and Joaquín Ibáñez Ulargui take the reader on an interesting journey featuring Michael Florent van Langren and the first (?) instance of data visualization in “The First (Known) Statistical Graph: Michael Florent van Langren and the ‘Secret’ of Longitude.”

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                                One Comment »

                                • Jaime Zamora Alvarado said:

                                  Hello frthieds,

                                  I have the book called Minitab Manual for business statistics by Norean R. Sharpe, Richard De Veaux and Paul Velleman.
                                  I want to know the website for get the data because is not very clear on the viii Introduction page.
                                  Can you help me?.

                                  Thanks very much
                                  Jaime Zamora Alvarado.

                                  February 22, 2011