Incorporating the latest R packages as well as new case studies and applications, Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition covers the aspects of R most often used by statistical analysts. New users of R will find the book's simple approach easy to understand while more sophisticated users will appreciate the invaluable source of task-oriented information.
New to the Second Edition
The use of RStudio, which increases the productivity of R users and helps users avoid error-prone cut-and-paste workflows
New chapter of case studies illustrating examples of useful data management tasks, reading complex files, making and annotating maps, "scraping" data from the web, mining text files, and generating dynamic graphics
New chapter on special topics that describes key features, such as processing by group, and explores important areas of statistics, including Bayesian methods, propensity scores, and bootstrapping
New chapter on simulation that includes examples of data generated from complex models and distributions
A detailed discussion of the philosophy and use of the knitr and markdown packages for R
New packages that extend the functionality of R and facilitate sophisticated analyses
Reorganized and enhanced chapters on data input and output, data management, statistical and mathematical functions, programming, high-level graphics plots, and the customization of plots
Easily Find Your Desired Task
Conveniently organized by short, clear descriptive entries, this edition continues to show users how to easily perform an analytical task in R. Users can quickly find and implement the material they need through the extensive indexing, cross-referencing, and worked examples in the text. Datasets and code are available for download on a supplementary website.
Автор: Xia Yinglin, Sun Jun, Chen Ding-Geng Название: Statistical Analysis of Microbiome Data with R ISBN: 9811315337 ISBN-13(EAN): 9789811315336 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Chapter 1: Introduction to R, RStudio and ggplot2 1.1 Introduction to R 1.2 Introduction to RStudio 1.3 Introduction to ggplot2 1.4 Introduction to R Packages for Microbiome Data Chapter 2: What are Microbiome Data?2.1 Phylogenetics--The Basics 2.2 What Microbiome Data Look Like? 2.2.1 Basic Data Structure and Format of Microbiome Data 2.2.2 OUT Table2.2 3 Response Variables and Covariates2.3 Some Specific Features of Microbiome Data Chapter 3: Bioinformatic and Statistical Analyses of Microbiome Data 3.1 Overview of Bioinformatic Analysis 3.1.1 Taxonomic Diversity: from the 16S-based Approach 3.1.2 Taxonomic Profiling of Shotgun Metagenomes3.1.3 Introduction to Bioinformatic toolso QIIME o Mothuro 16S rRNA Gene Sequence Data Analysis using QIIME and Mothuro Other Biostatistics Tools3.2 Statistical Analysis of Microbiome Community Composition 3.2.1 Alpha Diversity Analysis and Statistical Measurements 3.2.2 Beta Diversity Analysis and Statistical Measurements3.3 Multivariate Statistical Techniques 3.3.1Data Visualization: Principal Component and Principal Coordinates Analyses 3.3.2 Classification and Clustering with Visualization 3.4 Hypothesis Testing and Statistical Modeling 3.4.1 Statistical Testing of Microbiome Community 3.4.2 Multivariate Statistical Methods and Modeling of Microbiome Community and Environmental Covariates3.4.3 Mediational and Longitudinal Microbiome Data Analysis3.4.4 Host Interactions and Interventions3.4.5 Mediation Analysis and Longitudinal Analysis 3.5 Multiple Comparisons and Testing Correlation 3.6 Correlation Analysis of Microbiome Community and Environmental Covariates Chapter 4: Power and Sample Size Calculation in Hypothesis Testing Microbiome Data4.1 Statistical Hypothesis Testing and Power Analysis 4.1.1 Hypothesis Testing 4.1.2 Power Analysis and Sample Size Calculation4.2 Comparing Diversity or a Taxon of Interest between Two Groups 4.2.1 Hypotheses and Basic Power and Sample Size Formulas4.2.2 Diversity Data for Vitamin D and Vitamin D Receptor Study4.2.3 Theory of Power for a Test for Comparing Proportions4.2.4 Power of Fisher's Exact Test for Comparing Proportions4.2.5 R Function power.t.test4.3 Comparing Diversity across More than Two Groups 4.3.1 Hypotheses and Theory of Power for One-Way ANOVA4.3.2 Examples4.3.2 R Function pwr.avova.test4.4 Comparing the Frequency of all Taxa across Groups4.4.1 Hypotheses Testing and Power and Sample Size Calculations for Comparing all Taxa4.4.2 Dirichlet-multinomial model in Power and Sample Size Analyses4.4.3 Power and Size Calculations using HMP Package4.5 Power and Sample Size Estimation using Pairwise Distances and PERMANOVA 4.5.1 PERMANOVA and Estimation of PERMANOVA Power 4.5.2 Examples using micropower Package4.6 Power Calculations using ANOSIM Package Chapter 5: Microbiome Data Management5.1 Data Importing and Merging datasets or components 5.1.1 Importing the Output from QIIME 5.1.2 Importing the Output from mothur&
Автор: Richard M. Heiberger; Burt Holland Название: Statistical Analysis and Data Display ISBN: 149397968X ISBN-13(EAN): 9781493979684 Издательство: Springer Рейтинг: Цена: 107130.00 T Наличие на складе: Нет в наличии.
The inverse obstacle scattering problem consists of finding the unknown surface of a body (obstacle) from the scattering (;;), where (;;) is the scattering amplitude; is the direction of the scattered, incident wave, respectively, is the unit sphere in the ℝ3 and k > 0 is the modulus of the wave vector.
The scattering data is called non-over-determined if its dimensionality is the same as the one of the unknown object. By the dimensionality one understands the minimal number of variables of a function describing the data or an object. In an inverse obstacle scattering problem this number is 2, and an example of non-over-determined data is (): = (;₀;₀). By sub-index 0 a fixed value of a variable is denoted.
It is proved in this book that the data (), known for all in an open subset of , determines uniquely the surface and the boundary condition on . This condition can be the Dirichlet, or the Neumann, or the impedance type.
The above uniqueness theorem is of principal importance because the non-over-determined data are the minimal data determining uniquely the unknown . There were no such results in the literature, therefore the need for this book arose. This book contains a self-contained proof of the existence and uniqueness of the scattering solution for rough surfaces.
Название: Open source software for statistical analysis of big data ISBN: 1799827682 ISBN-13(EAN): 9781799827689 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 201430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Presents research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. The book features coverage on a broad range of topics, including cluster analysis, time series forecasting, and machine learning.
Автор: Alemi Farrokh Название: Big Data in Healthcare: Statistical Analysis of the Electronic Health Record ISBN: 1640550631 ISBN-13(EAN): 9781640550636 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 85010.00 T Наличие на складе: Невозможна поставка. Описание: Big Data in Healthcare: Statistical Analysis of the Electronic Health Record provides the statistical tools that healthcare leaders need to organize and interpret their data. Designed for accessibility to those with a limited mathematics background, the book demonstrates how to leverage EHR data for applications as diverse as healthcare marketing, pay for performance, cost accounting, and strategic management. Topics include:
Using real-world data to compare hospitals' performance.
Measuring the prognosis of patients through massive data
Distinguishing between fake claims and true improvements
Comparing the effectiveness of different interventions using causal analysis
Benchmarking different clinicians on the same set of patients
Remove confounding in observational data
This book can be used in introductory courses on hypothesis testing, intermediate courses on regression, and advanced courses on causal analysis. It can also be used to learn SQL language. Its extensive online instructor resources include course syllabi, PowerPoint and video lectures, Excel exercises, individual and team assignments, answers to assignments, and student-organized tutorials. Big Data in Healthcare applies the building blocks of statistical thinking to the basic challenges that healthcare leaders face every day. Prepare for those challenges with the clear understanding of your data that statistical analysis can bring - and make the best possible decisions for maximum performance in the competitive field of healthcare.
Автор: Carlo Bertoluzza; Maria A. Gil; Dan A. Ralescu Название: Statistical Modeling, Analysis and Management of Fuzzy Data ISBN: 3790825018 ISBN-13(EAN): 9783790825015 Издательство: Springer Рейтинг: Цена: 153720.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The contributions in this book state the complementary rather than competitive relationship between Probability and Fuzzy Set Theory and allow solutions to real life problems with suitable combinations of both theories.
Автор: Pierre Duchesne; Bruno R?millard Название: Statistical Modeling and Analysis for Complex Data Problems ISBN: 144193751X ISBN-13(EAN): 9781441937513 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Statistical Modeling and Analysis for Complex Data Problems treats some of today's more complex problems and it reflects some of the important research directions in the field. Twenty-nine authors - largely from Montreal's GERAD Multi-University Research Center and who work in areas of theoretical statistics, applied statistics, probability theory, and stochastic processes - present survey chapters on various theoretical and applied problems of importance and interest to researchers and students across a number of academic domains.
Автор: Isra?l C?sar Lerman Название: Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering ISBN: 1447167910 ISBN-13(EAN): 9781447167914 Издательство: Springer Рейтинг: Цена: 153720.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Preface.- On Some Facets of the Partition Set of a Finite Set.- Two Methods of Non-hierarchical Clustering.- Structure and Mathematical Representation of Data.- Ordinal and Metrical Analysis of the Resemblance Notion.- Comparing Attributes by a Probabilistic and Statistical Association I.- Comparing Attributes by a Probabilistic and Statistical Association II.- Comparing Objects or Categories Described by Attributes.- The Notion of "Natural" Class, Tools for its Interpretation. The Classifiability Concept.- Quality Measures in Clustering.- Building a Classification Tree.- Applying the LLA Method to Real Data.- Conclusion and Thoughts for Future Works
Автор: Saito Название: Data Analysis of Asymmetric Structures ISBN: 0824753984 ISBN-13(EAN): 9780824753986 Издательство: Taylor&Francis Рейтинг: Цена: 148010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Offers a comprehensive presentation of a variety of models and theories for the analysis of asymmetry and its applications. This work details theories, methods, and models for the analysis of asymmetric structures in a variety of disciplines and presents opportunities and challenges affecting research developments and business applications.
Название: Open source software for statistical analysis of big data ISBN: 1799827690 ISBN-13(EAN): 9781799827696 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 152460.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Presents research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. The book features coverage on a broad range of topics, such as cluster analysis, time series forecasting, and machine learning.
Автор: Susan B. Gerber; Kristin E. Voelkl Название: The SPSS Guide to the New Statistical Analysis of Data ISBN: 038794821X ISBN-13(EAN): 9780387948218 Издательство: Springer Рейтинг: Цена: 97820.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This companion to The New Statistical Analysis of Data by Anderson and Finn provides a hands-on guide to data analysis using SPSS. First, the authors provide a brief review of using SPSS, and then, corresponding to the organisation of The New Statistical Analysis of Data, readers participate in analysing many of the data sets discussed in the book.
Казахстан, 010000 г. Астана, проспект Туран 43/5, НП2 (офис 2) ТОО "Логобук" Тел:+7 707 857-29-98 ,+7(7172) 65-23-70 www.logobook.kz
