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Probabilities. Mathematical statistics

  • Statistical Methods for Spatial Data Analysisby Oliver Schabenberger; Carol A. Gotway

    CRC Press 2017; US$ 115.95

    Understanding spatial statistics requires tools from applied and mathematical statistics, linear model theory, regression, time series, and stochastic processes. It also requires a mindset that focuses on the unique characteristics of spatial data and the development of specialized analytical tools designed explicitly for spatial data analysis. Statistical... more...

  • Introduction to Probability with Texas Hold’em Examplesby Frederic Paik Schoenberg

    CRC Press 2016; US$ 56.95

    Introduction to Probability with Texas Hold’em Examples illustrates both standard and advanced probability topics using the popular poker game of Texas Hold’em, rather than the typical balls in urns. The author uses students’ natural interest in poker to teach important concepts in probability. This classroom-tested book covers the main subjects... more...

  • Standard Deviationsby Gary Smith

    Gerald Duckworth & Co 2016; US$ 11.99

    Did you know that having a messy room will make you racist? Or that human beings possess the ability to postpone death until after important ceremonial occasions? Or that people live three to five years longer if they have positive initials, like ACE? All of these ‘facts’ have been argued with a straight face by researchers and backed up with reams... more...

  • Applied Iterative Methodsby Louis A. Hageman

    Elsevier Science 2016; US$ 72.95

    Applied Iterative Methods more...

  • Multiple Factor Analysis by Example Using Rby Jérôme Pagès

    CRC Press 2016; US$ 89.95

    Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also... more...

  • Displaying Time Series, Spatial, and Space-Time Data with Rby Oscar Perpinan Lamigueiro

    CRC Press 2016; US$ 79.95

    Code and Methods for Creating High-Quality Data Graphics A data graphic is not only a static image, but it also tells a story about the data. It activates cognitive processes that are able to detect patterns and discover information not readily available with the raw data. This is particularly true for time series, spatial, and space-time datasets.... more...

  • Statistical Computing with Rby Maria L. Rizzo

    CRC Press 2016; US$ 99.95

    Computational statistics and statistical computing are two areas that employ computational, graphical, and numerical approaches to solve statistical problems, making the versatile R language an ideal computing environment for these fields. One of the first books on these topics to feature R, Statistical Computing with R covers the traditional core... more...

  • Developments in Statisticsby Paruchuri R. Krishnaiah

    Elsevier Science 2016; US$ 72.95

    Development in Statistics, Volume 2 is a collection of papers that deals with one- and two- dimensional structures, the statistical theory of linear systems, bispectra, and energy transfer in grid-generated turbulence. Several papers discuss simultaneous test procedures, stochastic Markovian fields, as well as the stopping of invariant sequential probability... more...

  • Handbook of Fitting Statistical Distributions with Rby Zaven A. Karian; Edward J. Dudewicz

    CRC Press 2016; US$ 199.95

    With the development of new fitting methods, their increased use in applications, and improved computer languages, the fitting of statistical distributions to data has come a long way since the introduction of the generalized lambda distribution (GLD) in 1969. Handbook of Fitting Statistical Distributions with R presents the latest and best methods,... more...

  • Introduction to the Theory of Statistical Inferenceby Hannelore Liero; Silvelyn Zwanzig

    CRC Press 2016; US$ 81.95

    Based on the authors’ lecture notes, Introduction to the Theory of Statistical Inference presents concise yet complete coverage of statistical inference theory, focusing on the fundamental classical principles. Suitable for a second-semester undergraduate course on statistical inference, the book offers proofs to support the mathematics. It illustrates... more...