Description

Book Synopsis
Integrating computers into mathematical statistics courses allows students to simulate experiments and visualize their results, handle larger data sets, analyze data more quickly, and compare the results of classical methods of data analysis with those using alternative techniques. This text presents a concise introduction to the concepts of probability theory and mathematical statistics. The accompanying in-class and take-home computer laboratory activities reinforce the techniques introduced in the text and are accessible to students with little or no experience with Mathematica. These laboratory materials present applications in a variety of real-world settings, with data from epidemiology, environmental sciences, medicine, social sciences, physical sciences, manufacturing, engineering, marketing, and sports. Included in the book are parametric, nonparametric, permutation, bootstrap and diagnostic methods. Permutation and bootstrap methods are discussed side by side with classical m

Mathematica Laboratories for Mathematical

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    £80.96

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    RRP £89.95 – you save £8.99 (9%)

    Order before 4pm tomorrow for delivery by Sat 20 Jun 2026.

    By Jenny A. Baglivo

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      View other formats and editions of Mathematica Laboratories for Mathematical by Jenny A. Baglivo

      Publisher: Society for Industrial and Applied Mathematics
      Publication Date: 11/1/2004
      ISBN13: 9780898715668, 978-0898715668
      ISBN10: 0898715660

      Description

      Book Synopsis
      Integrating computers into mathematical statistics courses allows students to simulate experiments and visualize their results, handle larger data sets, analyze data more quickly, and compare the results of classical methods of data analysis with those using alternative techniques. This text presents a concise introduction to the concepts of probability theory and mathematical statistics. The accompanying in-class and take-home computer laboratory activities reinforce the techniques introduced in the text and are accessible to students with little or no experience with Mathematica. These laboratory materials present applications in a variety of real-world settings, with data from epidemiology, environmental sciences, medicine, social sciences, physical sciences, manufacturing, engineering, marketing, and sports. Included in the book are parametric, nonparametric, permutation, bootstrap and diagnostic methods. Permutation and bootstrap methods are discussed side by side with classical m

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