One Hundred Physics Visualizations Using MATLAB, Green Dan

Автор: Jones
Название: Avoiding Data Pitfalls: How to steer clear of comm on blunders when working with data and presenting analysis and visualizations
ISBN: 1119278163 ISBN-13(EAN): 9781119278160
Издательство: Wiley
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Цена: 40120.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Avoid data blunders and create truly useful visualizations Avoiding Data Pitfalls is a reputation-saving handbook for those who work with data, designed to help you avoid the all-too-common blunders that occur in data analysis, visualization, and presentation.

Название: Primer in Biological Data Analysis and Visualization Using R
ISBN: 0231166990 ISBN-13(EAN): 9780231166997
Издательство: Wiley
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Цена: 33790.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Drawing on Gregg Hartvigsen`s extensive experience teaching biostatistics and modeling biological systems, this text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences.

Автор: Holland
Название: Graphics and GUIs with MATLAB, Third Edition
ISBN: 1584883200 ISBN-13(EAN): 9781584883203
Издательство: Taylor&Francis
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Цена: 76550.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents MATLAB version 6.x, including its integrated development desktop, enhanced computational engine, and interfaces to external languages. This title includes two chapters that address data visualization and GUI design, and together they provide an understanding of when to use GUIs and what works well graphically in various situations.

Автор: Mirman
Название: Growth Curve Analysis and Visualization Using R
ISBN: 1466584327 ISBN-13(EAN): 9781466584327
Издательство: Taylor&Francis
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Цена: 91860.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Learn How to Use Growth Curve Analysis with Your Time Course Data An increasingly prominent statistical tool in the behavioral sciences, multilevel regression offers a statistical framework for analyzing longitudinal or time course data. It also provides a way to quantify and analyze individual differences, such as developmental and neuropsychological, in the context of a model of the overall group effects. To harness the practical aspects of this useful tool, behavioral science researchers need a concise, accessible resource that explains how to implement these analysis methods. Growth Curve Analysis and Visualization Using R provides a practical, easy-to-understand guide to carrying out multilevel regression/growth curve analysis (GCA) of time course or longitudinal data in the behavioral sciences, particularly cognitive science, cognitive neuroscience, and psychology. With a minimum of statistical theory and technical jargon, the author focuses on the concrete issue of applying GCA to behavioral science data and individual differences. The book begins with discussing problems encountered when analyzing time course data, how to visualize time course data using the ggplot2 package, and how to format data for GCA and plotting. It then presents a conceptual overview of GCA and the core analysis syntax using the lme4 package and demonstrates how to plot model fits. The book describes how to deal with change over time that is not linear, how to structure random effects, how GCA and regression use categorical predictors, and how to conduct multiple simultaneous comparisons among different levels of a factor. It also compares the advantages and disadvantages of approaches to implementing logistic and quasi-logistic GCA and discusses how to use GCA to analyze individual differences as both fixed and random effects. The final chapter presents the code for all of the key examples along with samples demonstrating how to report GCA results. Throughout the book, R code illustrates how to implement the analyses and generate the graphs. Each chapter ends with exercises to test your understanding. The example datasets, code for solutions to the exercises, and supplemental code and examples are available on the author’s website.