Download or read book An lisis de datos con el programa estad stico R written by Christian Salas-Eljatib and published by . This book was released on 2021 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Gu a para el an lisis estad stico con R Commander written by Victoria Alea Riera and published by Edicions Universitat Barcelona. This book was released on 2014-09-05 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: El programa estadístico R Commander, gratuito y de libre acceso, se utiliza actualmente en muchas universidades y en la mayoría de centros de investigación, constituyendo una valiosa herramienta de estudio en el ámbito de las ciencias sociales, económicas y empresariales, entre otras. En esta guía se explican las posibilidades del programa, tanto su funcionamiento como los diferentes modelos estadísticos, y se ofrece un conjunto de bases de datos que permiten la realización y la comprobación de los diferentes ejemplos expuestos. El libro, en definitiva, pone al alcance de cualquier lector, y especialmente de los estudiantes de universitarios de estadística, una descripción práctica de un programa cuyo uso, cada vez más extendido, está ayudando a mejorar el análisis de la información sobre la realidad que nos rodea.
Download or read book Software for Data Analysis written by John Chambers and published by Springer Science & Business Media. This book was released on 2008-06-14 with total page 515 pages. Available in PDF, EPUB and Kindle. Book excerpt: John Chambers turns his attention to R, the enormously successful open-source system based on the S language. His book guides the reader through programming with R, beginning with simple interactive use and progressing by gradual stages, starting with simple functions. More advanced programming techniques can be added as needed, allowing users to grow into software contributors, benefiting their careers and the community. R packages provide a powerful mechanism for contributions to be organized and communicated. This is the only advanced programming book on R, written by the author of the S language from which R evolved.
Download or read book Datos composicionales y su an lisis mediante R written by Diego Campos and published by GRIN Verlag. This book was released on 2015-05-13 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tesis del año 2011 en eltema Economía - Estadísticas y métodos, Nota: 7, , Idioma: Español, Resumen: Los datos composicionales se caracterizan por ser vectores aleatorios de componentes positivas y de suma constante (100, 1, un millón, etc.). En Geología, Petrología, Química, Economía, etc., es habitual trabajar con vectores de datos cuyas componentes representan la contribución relativa de diferentes partes en relación a un total, dando lugar a muestras composicionales. Con frecuencia aparecen medidas de esta índole, por ejemplo: - Ciencias de la tierra (geoquímica, petrología, etc.): El estudio composicional de un cierto tipo de bencina (compuesto de Etano, Metano, etc.). - Biología: El estudio composicional en una muestra de sangre (sustancias minerales como la glucosa, el colesterol, la urea, el calcio, el fósforo y el ácido úrico, entre otros). - Ciencias ambientales: El análisis composicional de contaminación en una cierta ciudad (distintos tipo de variables que influyen en la contaminación). - Economía: Análisis de Stock Per-Cápita en una muestra de países. Este tipo de problemas tienen una característica en común, que es poseer variables con una cierta escala (la medida no es necesariamente la misma), donde la suma total de todas las variables de cada observación, no precisamente suman un 100%, debiendo asignar un peso a cada variable para cada una de las observaciones. Esta situación provoca la inadecuación de los métodos estadísticos clásicos, así, el interés por disponer de herramientas adecuadas para éste tipo de análisis se hace fundamental. El problema del análisis estadístico de datos composicionales ha sido y es una fuente de preocupación para muchos científicos desde que en 1897 Karl Pearson pusiera de manifiesto la inadecuación de los métodos estadísticos clásicos para el estudio de los mismos. [...]
Download or read book An lisis de datos con power bi r rstudio y knime written by Irma Yolanda Polanco and published by Ediciones de la U. This book was released on 2022-12-15 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Este libro, condensa y adapta distintas prácticas y ejemplos de las herramientas más utilizadas en el análisis de datos: Power BI Desktop, R – RStudio y Knime. El capítulo 1, Prácticas con Power BI, se describe la conexión a datos, creación de un modelo de datos, creación de objetos visuales, trabajo con informes. Todo ello acompañado de prácticas de análisis de datos financieros, análisis de una página web (Eurocopa), combinar datos, creación de medidas propias y análisis de datos de una supertienda. El capítulo 2, Prácticas con R y RStudio, se describe el entorno de desarrollo y las características generales, donde se destaca: tipos de datos, carga de datos y prácticas de análisis de datos como: estadística descriptiva de una variable cuantitativa continua, regresión lineal, árboles de decisión y minería de texto. El capítulo 3, Prácticas con Knime, se inicia con la introducción a Knime Analytics donde se destaca: ventanas, nodos y flujo de trabajo y creación de un proyecto Knime. Se termina el capítulo con la descripción de las diferentes prácticas que involucran: ciencia de datos, modelo de entrenamiento de clasificación de datos y modelo de predicción de supervivencia del Titanic. Finalmente, se presenta la solución de todos los ejercicios planteados en las prácticas desarrolladas.
Download or read book Learning R written by Richard Cotton and published by "O'Reilly Media, Inc.". This book was released on 2013-09-09 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, youâ??ll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts. The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includes a quiz on what youâ??ve learned, and concludes with exercises, most of which involve writing R code. Write a simple R program, and discover what the language can do Use data types such as vectors, arrays, lists, data frames, and strings Execute code conditionally or repeatedly with branches and loops Apply R add-on packages, and package your own work for others Learn how to clean data you import from a variety of sources Understand data through visualization and summary statistics Use statistical models to pass quantitative judgments about data and make predictions Learn what to do when things go wrong while writing data analysis code
Download or read book AN LISIS ESTAD STICO DE DATOS a trav s de R written by Cesar Perez Lopez and published by Independently Published. This book was released on 2019-05-20 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: R es un programa enfocado fundamentalmente al análisis estadístico de datos. En este libro se tratan las facetas más importante del análisis de datos aplicado con R, incluyendo el análisis exploratorio de datos, la estadística descriptiva, gráficos, modelos de regresión, modelos lineales generalizados, modelos del análisis de la varianza, técnicas de reducción de la dimensión, componentes principales, análisis factorial, análisis clúster y otros temas del análisis multivariante de datos
Download or read book Miner a de texto con R written by GIL PASCUAL Juan Antonio and published by Editorial UNED. This book was released on 2021-09-20 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: En el contexto de la sociedad actual de la información los datos no estructurados toman especial relevancia. El extraer información relevante de opiniones volcadas en páginas web resulta de encuestas a usuarios de hoteles, restaurantes, centros comerciales, centros docentes, etc. Influyen de forma decisiva en las orientaciones comerciales de los mismos. En suma, aquellos registros de información textual donde el tratamiento de los mismos de forma manual resulta en cierta forma inabordable necesitan de una herramienta de ayuda. Para conseguir ese fin existe un conjunto de paquetes del programa informático-estadístico R que dan solución global a las necesidades de captar y tratar la información relevante obtenida. Por tanto, la minería de textos con R tiene como objetivo general facilitar la extracción y tratamiento de información textual para la investigación, siendo herramientas estadísticas de minería de datos las que completan el proceso. El texto que se presenta aborda, con la ayuda del programa R, en seis temas las tareas fundamentales del proceso de extracción y tratamiento de datos textuales. En primer lugar, se fijan los conceptos básicos en minería textual con R; después se habla de procesos primarios con los textos. Con estos dos capítulos se tienen los rudimentos básicos para cualquier tratamiento posterior del texto. En el capítulo tres se habla de las técnicas descriptivas de minería textual y en el capítulo cuatro de las técnicas explicativas. Finalmente los temas cinco y seis están dedicados a detallar ejemplos prácticos de aplicaciones de minería textual en: análisis de opiniones, análisis de estilo, pruebas y exámenes automatizados o parametrizados, tratamiento de información de twitter, análisis de redes sociales y extracción de información de la web (web scraping). No se ha pretendido ser exhaustivo en las aplicaciones de minería textual por limitaciones de espacio, simplemente se ha puesto las que se piensa son más utilizadas. La visión del texto es eminentemente práctica, con múltiples códigos para resolver los numerosos ejemplos lo que facilita una posterior aplicación en contextos personales del lector. Para su comprensión se supone un conocimiento elemental de R y cierta familiaridad con términos estadísticos básicos.
Download or read book Analysis of Categorical Data with R written by Christopher R. Bilder and published by CRC Press. This book was released on 2014-08-11 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn How to Properly Analyze Categorical Data Analysis of Categorical Data with R presents a modern account of categorical data analysis using the popular R software. It covers recent techniques of model building and assessment for binary, multicategory, and count response variables and discusses fundamentals, such as odds ratio and probability estimation. The authors give detailed advice and guidelines on which procedures to use and why to use them. The Use of R as Both a Data Analysis Method and a Learning Tool Requiring no prior experience with R, the text offers an introduction to the essential features and functions of R. It incorporates numerous examples from medicine, psychology, sports, ecology, and other areas, along with extensive R code and output. The authors use data simulation in R to help readers understand the underlying assumptions of a procedure and then to evaluate the procedure’s performance. They also present many graphical demonstrations of the features and properties of various analysis methods. Web Resource The data sets and R programs from each example are available at www.chrisbilder.com/categorical. The programs include code used to create every plot and piece of output. Many of these programs contain code to demonstrate additional features or to perform more detailed analyses than what is in the text. Designed to be used in tandem with the book, the website also uniquely provides videos of the authors teaching a course on the subject. These videos include live, in-class recordings, which instructors may find useful in a blended or flipped classroom setting. The videos are also suitable as a substitute for a short course.
Download or read book R by Example written by Jim Albert and published by Springer Science & Business Media. This book was released on 2012-01-28 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: R by Example is an example-based introduction to the statistical computing environment that does not assume any previous familiarity with R or other software packages. R functions are presented in the context of interesting applications with real data. The purpose of this book is to illustrate a range of statistical and probability computations using R for people who are learning, teaching, or using statistics. Specifically, this book is written for users who have covered at least the equivalent of (or are currently studying) undergraduate level calculus-based courses in statistics. These users are learning or applying exploratory and inferential methods for analyzing data and this book is intended to be a useful resource for learning how to implement these procedures in R.
Download or read book Analyzing Compositional Data with R written by K. Gerald van den Boogaart and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the statistical analysis of compositional data sets, i.e., data in percentages, proportions, concentrations, etc. The subject is covered from its grounding principles to the practical use in descriptive exploratory analysis, robust linear models and advanced multivariate statistical methods, including zeros and missing values, and paying special attention to data visualization and model display issues. Many illustrated examples and code chunks guide the reader into their modeling and interpretation. And, though the book primarily serves as a reference guide for the R package “compositions,” it is also a general introductory text on Compositional Data Analysis. Awareness of their special characteristics spread in the Geosciences in the early sixties, but a strategy for properly dealing with them was not available until the works of Aitchison in the eighties. Since then, research has expanded our understanding of their theoretical principles and the potentials and limitations of their interpretation. This is the first comprehensive textbook addressing these issues, as well as their practical implications with regard to software. The book is intended for scientists interested in statistically analyzing their compositional data. The subject enjoys relatively broad awareness in the geosciences and environmental sciences, but the spectrum of recent applications also covers areas like medicine, official statistics, and economics. Readers should be familiar with basic univariate and multivariate statistics. Knowledge of R is recommended but not required, as the book is self-contained.
Download or read book R in Action Third Edition written by Robert I. Kabacoff and published by Simon and Schuster. This book was released on 2022-06-28 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: R is the most powerful tool you can use for statistical analysis. This definitive guide smooths R’s steep learning curve with practical solutions and real-world applications for commercial environments. In R in Action, Third Edition you will learn how to: Set up and install R and RStudio Clean, manage, and analyze data with R Use the ggplot2 package for graphs and visualizations Solve data management problems using R functions Fit and interpret regression models Test hypotheses and estimate confidence Simplify complex multivariate data with principal components and exploratory factor analysis Make predictions using time series forecasting Create dynamic reports and stunning visualizations Techniques for debugging programs and creating packages R in Action, Third Edition makes learning R quick and easy. That’s why thousands of data scientists have chosen this guide to help them master the powerful language. Far from being a dry academic tome, every example you’ll encounter in this book is relevant to scientific and business developers, and helps you solve common data challenges. R expert Rob Kabacoff takes you on a crash course in statistics, from dealing with messy and incomplete data to creating stunning visualizations. This revised and expanded third edition contains fresh coverage of the new tidyverse approach to data analysis and R’s state-of-the-art graphing capabilities with the ggplot2 package. About the technology Used daily by data scientists, researchers, and quants of all types, R is the gold standard for statistical data analysis. This free and open source language includes packages for everything from advanced data visualization to deep learning. Instantly comfortable for mathematically minded users, R easily handles practical problems without forcing you to think like a software engineer. About the book R in Action, Third Edition teaches you how to do statistical analysis and data visualization using R and its popular tidyverse packages. In it, you’ll investigate real-world data challenges, including forecasting, data mining, and dynamic report writing. This revised third edition adds new coverage for graphing with ggplot2, along with examples for machine learning topics like clustering, classification, and time series analysis. What's inside Clean, manage, and analyze data Use the ggplot2 package for graphs and visualizations Techniques for debugging programs and creating packages A complete learning resource for R and tidyverse About the reader Requires basic math and statistics. No prior experience with R needed. About the author Dr. Robert I Kabacoff is a professor of quantitative analytics at Wesleyan University and a seasoned data scientist with more than 20 years of experience. Table of Contents PART 1 GETTING STARTED 1 Introduction to R 2 Creating a dataset 3 Basic data management 4 Getting started with graphs 5 Advanced data management PART 2 BASIC METHODS 6 Basic graphs 7 Basic statistics PART 3 INTERMEDIATE METHODS 8 Regression 9 Analysis of variance 10 Power analysis 11 Intermediate graphs 12 Resampling statistics and bootstrapping PART 4 ADVANCED METHODS 13 Generalized linear models 14 Principal components and factor analysis 15 Time series 16 Cluster analysis 17 Classification 18 Advanced methods for missing data PART 5 EXPANDING YOUR SKILLS 19 Advanced graphs 20 Advanced programming 21 Creating dynamic reports 22 Creating a package
Download or read book Data Analysis and Graphics Using R written by John Maindonald and published by Cambridge University Press. This book was released on 2003-08-04 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern statistical software systems provide sophisticated tools for researchers who need to manipulate and display their data. Using such systems requires training both in the software itself and in the statistical methods that it relies on. Concentrating on the freely available R system, this book demonstrates recently implemented approaches and methods in statistical analysis. The authors introduce elementary concepts in statistics through examples of real-world data analysis drawn from the authors' experience, both as teachers and as consultants. R code and data sets for all examples are available on the Internet. This emphasis on practical methodology combined with a tutorial approach makes the book accessible to anyone with a knowledge of undergraduate statistics, whether an upper-graduate student, a researcher, or a practising scientist or statistician. The methods demonstrated are suitable for use in a wide variety of disciplines, from social sciences to medicine, engineering and science.
Download or read book Computational Statistics written by Günther Sawitzki and published by CRC Press. This book was released on 2009-01-26 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Suitable for a compact course or self-study, Computational Statistics: An Introduction to R illustrates how to use the freely available R software package for data analysis, statistical programming, and graphics. Integrating R code and examples throughout, the text only requires basic knowledge of statistics and computing. This introduction covers one-sample analysis and distribution diagnostics, regression, two-sample problems and comparison of distributions, and multivariate analysis. It uses a range of examples to demonstrate how R can be employed to tackle statistical problems. In addition, the handy appendix includes a collection of R language elements and functions, serving as a quick reference and starting point to access the rich information that comes bundled with R. Accessible to a broad audience, this book explores key topics in data analysis, regression, statistical distributions, and multivariate statistics. Full of examples and with a color insert, it helps readers become familiar with R.
Download or read book R for Data Science written by Hadley Wickham and published by O'Reilly Media. This book was released on 2023-10-03 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use R to turn data into insight, knowledge, and understanding. Ideal for current and aspiring data scientists, this book introduces you to doing data science with R and RStudio, as well as the tidyverse--a collection of R packages designed to work together to make data science fast, fluent, and fun. Even if you have no programming experience, this updated edition will have you doing data science quickly. You'll learn how to import, transform, and visualize your data and communicate the results. And you'll get a complete, big-picture understanding of the data science cycle and the basic tools you need to manage the details. Each section in this edition includes exercises to help you practice what you've learned along the way. Updated for the latest tidyverse best practices, new chapters dive deeper into visualization and data wrangling, show you how to get data from spreadsheets, databases, and websites, and help you make the most of new programming tools. You'll learn how to: Visualize-create plots for data exploration and communication of results Transform-discover types of variables and the tools you can use to work with them Import-get data into R and in a form convenient for analysis Program-learn R tools for solving data problems with greater clarity and ease Communicate-integrate prose, code, and results with Quarto
Download or read book Business Analytics Using R A Practical Approach written by Umesh R Hodeghatta and published by Apress. This book was released on 2016-12-27 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn the fundamental aspects of the business statistics, data mining, and machine learning techniques required to understand the huge amount of data generated by your organization. This book explains practical business analytics through examples, covers the steps involved in using it correctly, and shows you the context in which a particular technique does not make sense. Further, Practical Business Analytics using R helps you understand specific issues faced by organizations and how the solutions to these issues can be facilitated by business analytics. This book will discuss and explore the following through examples and case studies: An introduction to R: data management and R functions The architecture, framework, and life cycle of a business analytics project Descriptive analytics using R: descriptive statistics and data cleaning Data mining: classification, association rules, and clustering Predictive analytics: simple regression, multiple regression, and logistic regression This book includes case studies on important business analytic techniques, such as classification, association, clustering, and regression. The R language is the statistical tool used to demonstrate the concepts throughout the book. What You Will Learn • Write R programs to handle data • Build analytical models and draw useful inferences from them • Discover the basic concepts of data mining and machine learning • Carry out predictive modeling • Define a business issue as an analytical problem Who This Book Is For Beginners who want to understand and learn the fundamentals of analytics using R. Students, managers, executives, strategy and planning professionals, software professionals, and BI/DW professionals.
