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Mathematical statistics; Data processing

Most popular at the top

  • Beginning Rby Mark Gardener

    Wiley 2012; US$ 34.99

    Conquer the complexities of this open source statistical language R is fast becoming the de facto standard for statistical computing and analysis in science, business, engineering, and related fields. This book examines this complex language using simple statistical examples, showing how R operates in a user-friendly context. Both students and... more...

  • Beginning Rby Larry Pace

    Apress 2012; US$ 39.99

    Beginning R: An Introduction to Statistical Programming is a hands-on book showing how to use the R language, write and save R scripts, build and import data files, and write your own custom statistical functions. R is a powerful open-source implementation of the statistical language S, which was developed by AT&T. R has eclipsed S and the commercially-available... more...

  • Behavioral Research Data Analysis with Rby Yuelin Li; Jonathan Baron

    Springer New York 2011; US$ 69.99

    This book is written for behavioral scientists who want to add the R programming language and software environment to their arsenal of statistical tools. The authors offer practical advice on widely-used statistical methods, using notes and annotated examples. more...

  • Big Data Analytics with R and Hadoopby Vignesh Prajapati

    Packt Publishing 2013; US$ 29.99

    Big Data Analytics with R and Hadoop is a tutorial style book that focuses on all the powerful big data tasks that can be achieved by integrating R and Hadoop.This book is ideal for R developers who are looking for a way to perform big data analytics with Hadoop. This book is also aimed at those who know Hadoop and want to build some intelligent applications... more...

  • Bioinformatics with R Cookbookby Paurush Praveen Sinha

    Packt Publishing 2014; US$ 32.99

    This book is an easy-to-follow, stepwise guide to handle real life Bioinformatics problems. Each recipe comes with a detailed explanation to the solution steps. A systematic approach, coupled with lots of illustrations, tips, and tricks will help you as a reader grasp even the trickiest of concepts without difficulty. This book is ideal for computational... more...

  • Competing Risks and Multistate Models with Rby Jan Beyersmann; Arthur Allignol; Martin Schumacher

    Springer New York 2011; US$ 69.99

    This book explains hazard-based analyses of competing risks and multistate data using the R statistical programming code, placing special emphasis on interpretation of results. Includes real data examples, and encourages readers to simulate their own data. more...

  • Computational Statistics Handbook with MATLAB, Second Editionby Wendy L. Martinez; Angel R. Martinez

    CRC Press 2007; US$ 109.95

    As with the bestselling first edition, Computational Statistics Handbook with MATLAB ® , Second Edition covers some of the most commonly used contemporary techniques in computational statistics. With a strong, practical focus on implementing the methods, the authors include algorithmic descriptions of the procedures as well as examples that illustrate... more...

  • Data Manipulation with Rby Jaynal Abedin

    Packt Publishing 2014; US$ 17.99

    This book is a step-by step, example-oriented tutorial that will show both intermediate and advanced users how data manipulation is facilitated smoothly using R.This book is aimed at intermediate to advanced level users of R who want to perform data manipulation with R, and those who want to clean and aggregate data effectively. Readers are expected... more...

  • Data Manipulation with Rby Jaynal Abedin; Kishor Kumar Das

    Packt Publishing 2015; US$ 23.99

    This book is for all those who wish to learn about data manipulation from scratch and excel at aggregating data effectively. It is expected that you have basic knowledge of R and have previously done some basic administration work with R. more...

  • Datenqualität erfolgreich steuernby Detlef Apel; Wolfgang Behme; Rüdiger Eberlein; Christian Merighi

    dpunkt.verlag 2015; US$ 52.48

    Immer mehr Unternehmen begreifen ein gutes Datenqualitätsmanagement als einen entscheidenden Wettbewerbsvorteil: Die IT-Kosten sinken, Projekte werden beschleunigt, auf Änderungen am Markt oder von gesetzlichen Auflagen kann schneller und flexibler reagiert werden. Datenintegrationen über System-, Abteilungs- und Unternehmensgrenzen hinweg werden erleichtert... more...