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The R Software


The R Software
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R Programming


R Programming
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Author : Daniel Daniel Bell
language : en
Publisher:
Release Date : 2020-06

R Programming written by Daniel Daniel Bell and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06 with categories.


2020- Second Edition, updated version. Get your copy!! Why Learn R? What are the reasons to learn R for Data Science? In this small textbook recommended for absolute beginners, the author tried to answer these types of questions. After reading this guide, maybe in one or two days, you will learn the basics of R programming and its utility for each Data Scientist. Indeed, R is a programming language and software environment for statistical analysis, graphics representation, and reporting. If you are trying to understand the R programming language as a beginner, this short book will give you enough understanding of almost all the concepts of the R language. The author will guide you through examples, how to program in R and how to use R for effective data analysis.Get your copy Now! Book Objectives This book is about R programming. The following are the objectives of the author: To familiarize you with the basics of R programming language. To help you understand the various fields where R can be applied and its use cases in each field. To equip you with R programming skills, both beginner and advanced skills. To introduce you to R programming for data analysis. To introduce you to R programming for machine learning. To help you understand and appreciate the power of R in statistical computing, data analysis, and scientific research. Who this Book is for? Anybody who is a complete beginner to R Programming. Anybody in need of advancing their R Programming skills. Professionals in computer programming. Professors, lecturers or tutors who are looking to find better ways to explain R programming to their students in the simplest and easiest way. Students and academicians, especially those focusing on R, Data Analysis,Machine Learning , computer science, and Databases development. Requirements The author expects you to have a computer installed with an operating system such as Linux, Windows or Mac OS X. What is inside the book? R BASICS R DATA TYPES R VARIABLES AND CONSTANTS R OPERATORS DECISION MAKING IN R R LOOPS R FUNCTIONS R CLASSES AND OBJECTS R FOR DATA SCIENCE R FOR MACHINE LEARNING From the Back Cover. R programming language is one of the most popular languages used by statisticians, data analysts, researchers to retrieve, clean, analyze, visualize and present data. This is a comprehensive book on how to get started with R programming, why you should learn it and how you can learn it. Daniel Bell begins by introducing the readers to the foundations of the R programming language. The aim is to help you understand, how the R interpreter works, the origin of the name R, how to set up the R programming environment, etc. The author has discussed the process of installing R on Windows, Linux and Mac OS. Moreover, the author has explored the basics of R programming including writing comments, using the R console, creating R script files, etc. The various features provided by R have been discussed in depth, including data types, variables, loops, decision making, functions, operators, classes, and objects, etc. The author has also discussed R for data science and R for machine learning. The book has been organized into chapters, with each chapter having many sub-chapters. R code scripts have been provided, alongside thorough explanations of the code and images showing the expected output upon the execution of every script. Get your copy



Learning R


Learning R
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Author : Richard Cotton
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2013-09-09

Learning R written by Richard Cotton and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-09 with Computers categories.


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



Statistical Programming With Sas Iml Software


Statistical Programming With Sas Iml Software
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Author : Rick Wicklin
language : en
Publisher: SAS Institute
Release Date : 2010-10-01

Statistical Programming With Sas Iml Software written by Rick Wicklin and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-10-01 with Computers categories.


Annotation SAS/IML software is a powerful tool for data analysts because it enables implementation of statistical algorithms that are not available in any SAS procedure. Rick Wicklin's Statistical Programming with SAS/IML Software is the first book to provide a comprehensive description of the software and how to use it. He presents tips and techniques that enable you to use the IML procedure and the SAS/IML Studio application efficiently. In addition to providing a comprehensive introduction to the software, the book also shows how to create and modify statistical graphs, call SAS procedures and R functions from a SAS/IML program, and implement such modern statistical techniques as simulations and bootstrap methods in the SAS/IML language. Written for data analysts working in all industries, graduate students, and consultants, Statistical Programming with SAS/IML Software includes numerous code snippets and more than 100 graphs.



A Beginner S Guide To Structural Equation Modeling


A Beginner S Guide To Structural Equation Modeling
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Author : Randall E. Schumacker
language : en
Publisher: Routledge
Release Date : 2015-12-22

A Beginner S Guide To Structural Equation Modeling written by Randall E. Schumacker and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-22 with Psychology categories.


Noted for its crystal clear explanations, this book is considered the most comprehensive introductory text to structural equation modeling (SEM). Noted for its thorough review of basic concepts and a wide variety of models, this book better prepares readers to apply SEM to a variety of research questions. Programming details and the use of algebra are kept to a minimum to help readers easily grasp the concepts so they can conduct their own analysis and critique related research. Featuring a greater emphasis on statistical power and model validation than other texts, each chapter features key concepts, examples from various disciplines, tables and figures, a summary, and exercises. Highlights of the extensively revised 4th edition include: -Uses different SEM software (not just Lisrel) including Amos, EQS, LISREL, Mplus, and R to demonstrate applications. -Detailed introduction to the statistical methods related to SEM including correlation, regression, and factor analysis to maximize understanding (Chs. 1 – 6). -The 5 step approach to modeling data (specification, identification, estimation, testing, and modification) is now covered in more detail and prior to the modeling chapters to provide a more coherent view of how to create models and interpret results (ch. 7). -More discussion of hypothesis testing, power, sampling, effect sizes, and model fit, critical topics for beginning modelers (ch. 7). - Each model chapter now focuses on one technique to enhance understanding by providing more description, assumptions, and interpretation of results, and an exercise related to analysis and output (Chs. 8 -15). -The use of SPSS AMOS diagrams to describe the theoretical models. -The key features of each of the software packages (Ch. 1). -Guidelines for reporting SEM research (Ch. 16). -www.routledge.com/9781138811935 which provides access to data sets that can be used with any program, links to other SEM examples, related readings, and journal articles, and more. Reorganized, the new edition begins with a more detailed introduction to SEM including the various software packages available, followed by chapters on data entry and editing, and correlation which is critical to understanding how missing data, non-normality, measurement, and restriction of range in scores affects SEM analysis. Multiple regression, path, and factor models are then reviewed and exploratory and confirmatory factor analysis is introduced. These chapters demonstrate how observed variables share variance in defining a latent variables and introduce how measurement error can be removed from observed variables. Chapter 7 details the 5 SEM modeling steps including model specification, identification, estimation, testing, and modification along with a discussion of hypothesis testing and the related issues of power, and sample and effect sizes.Chapters 8 to 15 provide comprehensive introductions to different SEM models including Multiple Group, Second-Order CFA, Dynamic Factor, Multiple-Indicator Multiple-Cause, Mixed Variable and Mixture, Multi-Level, Latent Growth, and SEM Interaction Models. Each of the 5 SEM modeling steps is explained for each model along with an application. Chapter exercises provide practice with and enhance understanding of the analysis of each model. The book concludes with a review of SEM guidelines for reporting research. Designed for introductory graduate courses in structural equation modeling, factor analysis, advanced, multivariate, or applied statistics, quantitative techniques, or statistics II taught in psychology, education, business, and the social and healthcare sciences, this practical book also appeals to researchers in these disciplines. Prerequisites include an introduction to intermediate statistics that covers correlation and regression principles.



Survey Of Current Business


Survey Of Current Business
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Author :
language : en
Publisher:
Release Date : 2007

Survey Of Current Business written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Commercial statistics categories.




Data Driven Guide To The Analysis Of X Ray Photoelectron Spectra Using Rxpsg


Data Driven Guide To The Analysis Of X Ray Photoelectron Spectra Using Rxpsg
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Author : Giorgio Speranza
language : en
Publisher: CRC Press
Release Date : 2023-11-23

Data Driven Guide To The Analysis Of X Ray Photoelectron Spectra Using Rxpsg written by Giorgio Speranza and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-23 with Science categories.


This book provides a theoretical background to X-ray photoelectron spectroscopy (XPS) and a practical guide to the analysis of the XPS spectra using the RxpsG software, a powerful tool for XPS analysis. Although there are several publications and books illustrating the theory behind XPS and the origin of the spectral feature, this book provides an additional practical introduction to the use of RxpsG. It illustrates how to use the RxpsG software to perform specific key operations, with figures and examples which readers can reproduce themselves. The book contains a list of theoretical sections explaining the appearance of the various spectral features (core‐lines, Auger components, valence bands, loss features, etc.). They are accompanied by practical steps, so readers can learn how to analyze specific spectral features using the various functions of the RxpsG software. This book is a useful guide for researchers in physics, chemistry, and material science who are looking to begin using XPS, in addition to experienced researchers who want to learn how to use RxpsG. In the digital format, the spectral data and step-by-step indications are provided to reproduce the examples given in the textbook. RxpsG is a free software for the spectral analysis. Readers can find the installation information and download the package from https://github.com/GSperanza/ website. RxpsG was developed mainly by Giorgio Speranza with the help of his colleague dr. Roberto Canteri working at Fondazione Bruno Kessler. Key Features: Simplifies the use of RxpsG, how it works, and its applications. Demonstrates RxpsG using a reproduction of the graphical interface of RxpsG, showing the steps needed to perform a specific task and the effect on the XPS spectra. Accessible to readers without any prior experience using the RxpsG software. Giorgio Speranza is Senior Researcher at Fondazione Bruno Kessler – Trento Italy, Associate Member of the Italian National Council of Research, and Associate Member of the Department of Industrial Engineering at the University of Trento, Italy.



Spatial Statistics


Spatial Statistics
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Author : Mohammed A. Kalkhan
language : en
Publisher: CRC Press
Release Date : 2011-05-09

Spatial Statistics written by Mohammed A. Kalkhan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-05-09 with Mathematics categories.


Geospatial information modeling and mapping has become an important tool for the investigation and management of natural resources at the landscape scale. Spatial Statistics: GeoSpatial Information Modeling and Thematic Mapping reviews the types and applications of geospatial information data, such as remote sensing, geographic information systems



Food Security Poverty And Nutrition Policy Analysis


Food Security Poverty And Nutrition Policy Analysis
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Author : Suresh Babu
language : en
Publisher: Academic Press
Release Date : 2021-09-21

Food Security Poverty And Nutrition Policy Analysis written by Suresh Babu and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-21 with Technology & Engineering categories.


Food Security, Poverty and Nutrition Policy Analysis: Statistical Methods and Applications, Third Edition combines statistical data analysis and computer literacy, applying the results to develop policy alternatives through a series of statistical methods for real world food insecurity, malnutrition and poverty problems. The book presents the latest uses of statistical methods for policy analysis using the open source statistical environment R, in addition to having the original Stata files and applications. A new chapter on obesity brings in new datasets for analysis to effectively demonstrate the use of such data for addressing policy issues. Finally, program evaluation methods which can be directly applied to the data on food security, nutrition, poverty indicators and causal factors are included. This unique, real-world data takes the reader through a "hands-on" approach toward econometric practice whereby they can also test the effects of policy and program interventions. Further, this is the first book to explore actual data with STATA and R statistical packages that also provides a line-by-line guide to the programming and interpretation of results. - Provides a fully revised and updated tome on the latest technology, assessment advances and policy insights surrounding food security - Combines case-studies with data-based analysis - Includes self-contained, downloadable datasets, statistical appendices, computer programs, and interpretations of the results for policy applications



Structural Equation Modeling With Lavaan


Structural Equation Modeling With Lavaan
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Author : Kamel Gana
language : en
Publisher: John Wiley & Sons
Release Date : 2019-01-03

Structural Equation Modeling With Lavaan written by Kamel Gana and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-03 with Mathematics categories.


This book presents an introduction to structural equation modeling (SEM) and facilitates the access of students and researchers in various scientific fields to this powerful statistical tool. It offers a didactic initiation to SEM as well as to the open-source software, lavaan, and the rich and comprehensive technical features it offers. Structural Equation Modeling with lavaan thus helps the reader to gain autonomy in the use of SEM to test path models and dyadic models, perform confirmatory factor analyses and estimate more complex models such as general structural models with latent variables and latent growth models. SEM is approached both from the point of view of its process (i.e. the different stages of its use) and from the point of view of its product (i.e. the results it generates and their reading).



Methods For Monitoring Tiger And Prey Populations


Methods For Monitoring Tiger And Prey Populations
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Author : K. Ullas Karanth
language : en
Publisher: Springer
Release Date : 2017-10-26

Methods For Monitoring Tiger And Prey Populations written by K. Ullas Karanth and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-26 with Science categories.


This book addresses issues of monitoring populations of tigers, ungulate prey species and habitat occupancy, with relevance to similar assessments of large mammal species and general biodiversity. It covers issues of rigorous sampling, modeling, estimation and adaptive management of animal populations using cutting-edge tools, such as camera-traps, genetic identification and Geographic Information Systems (GIS), applied under the modern statistical approach of Bayesian and likelihood-based inference. Of special focus here are animal survey data derived for use under spatial capture-recapture, occupancy, distance sampling, mixture-modeling and connectivity analysees. Because tigers are an icons of global conservation, in last five decades,enormous amounts of commitment and resources have been invested by tiger range countries and the conservation community for saving wild tigers. However, status of the big cat remains precarious. Rigorous monitoring of surviving wild tiger populations continues to be essential for both understanding and recovering wild tigers. However, many tiger monitoring programs lack the necessary rigor to generate the reliable results. While the deployment of technologies, analyses, computing power and human-resource investments in tiger monitoring have greatly progressed in the last couple of decades, a full comprehension of their correct deployment has not kept pace in practice. In this volume, Dr. Ullas Karanth and Dr. James Nichols, world leaders in tiger biology and quantitative ecology, respectively, address this key challenge. The have collaborated with an extraordinary array of 30 scientists with expertise in a range of necessary disciplines - biology and ecology of tigers, prey and habitats; advanced statistical theory and practice; computation and programming; practical field-sampling methods that employ technologies as varied as camera traps, genetic analyses and geographic information systems. The book is a 'tour de force' of cutting-edge methodologies for assessing not just tigers but also other predators and their prey. The 14 chapters here are lucidly presented in a coherent sequence to provide tiger-specific answers to fundamental questions in animal population assessment: why monitor, what to monitor and how to monitor. While highlighting robust methods, the authors also clearly point out those that are in use, but unreliable. The managerial dimension of tiger conservation described here, the task of matching monitoring objectives with skills and resources to integrate tiger conservation under an adaptive framework, also renders this volume useful to wildlife scientists as well as conservationists.