Download or read book R FOR BASIC AND APPLIED SCIENCES written by JANARDHAN KADARI and published by Shashwat Publication. This book was released on 2023-11-22 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: R is a Statistcal programming language. R is Free and open source. R is an interpreted language not a compiled one. The R programming environment contains the range of tools for parallel computing, machine and deep learning and for working with big Data, including Torch and Tensar flow facilitating construction and implementation of neural networks. The Bioconductor repository contains over a thousand of software packages written in R for analyzing data sets from CDNA microarrays to copy-number variation and epigenomics (Robert Gentleman-Sorin Draghicia). Due to Data Handling and Modeling capabilities and its flexibility, R is becoming the most widely used software in bioinformatics. The R program is built from a variety of packages. These packages are libraries of commands. The Packages are available from the CRAN website. The current R is the result of a collaborative effort of the R core Group. R has many functions for statistical analysis and graphics. R has an effective data handling and storage facility. R provides operators for calculation on arrays, vectors, lists and matrices. This Book Covers all these with suitable examples. R has a collection of tools for data analysis. Keeping in view the Beginners apprehensions the Book provides the Salient Features of Descriptive Statistics & Covers the specific R tools for Statistical analysis. Throughout the Book examples are accompanied by R commands for easy reference. This Book Covers data handling, graphics, and a wide range of Statistical techniques. The Book would be of immense help to basic sciences, Engineering, Business Statistics, medicine streams, Biotechnology, Pharma, Bioinformatics, Genetics and Epidemiology.

Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

Download or read book Physical Chemistry for Engineering and Applied Sciences written by Frank R. Foulkes and published by CRC Press. This book was released on 2012-09-12 with total page 682 pages. Available in PDF, EPUB and Kindle. Book excerpt: Physical Chemistry for Engineering and Applied Sciences is the product of over 30 years of teaching first-year Physical Chemistry as part of the Faculty of Applied Science and Engineering at the University of Toronto. Designed to be as rigorous as compatible with a first-year student's ability to understand, the text presents detailed step-by-step

Download or read book An Introduction to Statistical Learning written by Gareth James and published by Springer Nature. This book was released on 2023-08-01 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.

Download or read book Applied Econometrics with R written by Christian Kleiber and published by Springer Science & Business Media. This book was released on 2008-12-10 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned routines. We believe that R has great potential in econometrics, both for research and for teaching. There are at least three reasons for this: (1) R is mostly platform independent and runs on Microsoft Windows, the Mac family of operating systems, and various ?avors of Unix/Linux, and also on some more exotic platforms. (2) R is free software that can be downloaded and installed at no cost from a family of mirror sites around the globe, the Comprehensive R Archive Network (CRAN); hence students can easily install it on their own machines. (3) R is open-source software, so that the full source code is available and can be inspected to understand what it really does, learn from it, and modify and extend it. We also like to think that platform independence and the open-source philosophy make R an ideal environment for reproducible econometric research.

Download or read book Learn R for Applied Statistics written by Eric Goh Ming Hui and published by Apress. This book was released on 2018-11-30 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gain the R programming language fundamentals for doing the applied statistics useful for data exploration and analysis in data science and data mining. This book covers topics ranging from R syntax basics, descriptive statistics, and data visualizations to inferential statistics and regressions. After learning R’s syntax, you will work through data visualizations such as histograms and boxplot charting, descriptive statistics, and inferential statistics such as t-test, chi-square test, ANOVA, non-parametric test, and linear regressions. Learn R for Applied Statistics is a timely skills-migration book that equips you with the R programming fundamentals and introduces you to applied statistics for data explorations. What You Will LearnDiscover R, statistics, data science, data mining, and big data Master the fundamentals of R programming, including variables and arithmetic, vectors, lists, data frames, conditional statements, loops, and functions Work with descriptive statistics Create data visualizations, including bar charts, line charts, scatter plots, boxplots, histograms, and scatterplots Use inferential statistics including t-tests, chi-square tests, ANOVA, non-parametric tests, linear regressions, and multiple linear regressions Who This Book Is For Those who are interested in data science, in particular data exploration using applied statistics, and the use of R programming for data visualizations.

Download or read book The R Book written by Michael J. Crawley and published by John Wiley & Sons. This book was released on 2007-06-13 with total page 953 pages. Available in PDF, EPUB and Kindle. Book excerpt: The high-level language of R is recognized as one of the mostpowerful and flexible statistical software environments, and israpidly becoming the standard setting for quantitative analysis,statistics and graphics. R provides free access to unrivalledcoverage and cutting-edge applications, enabling the user to applynumerous statistical methods ranging from simple regression to timeseries or multivariate analysis. Building on the success of the author’s bestsellingStatistics: An Introduction using R, The R Book ispacked with worked examples, providing an all inclusive guide to R,ideal for novice and more accomplished users alike. The bookassumes no background in statistics or computing and introduces theadvantages of the R environment, detailing its applications in awide range of disciplines. Provides the first comprehensive reference manual for the Rlanguage, including practical guidance and full coverage of thegraphics facilities. Introduces all the statistical models covered by R, beginningwith simple classical tests such as chi-square and t-test. Proceeds to examine more advance methods, from regression andanalysis of variance, through to generalized linear models,generalized mixed models, time series, spatial statistics,multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates andprofessionals in science, engineering and medicine. It is alsoideal for students and professionals in statistics, economics,geography and the social sciences.

Download or read book Applied Statistics with R written by Justin C. Touchon and published by Oxford University Press. This book was released on 2021-06-30 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: The statistical analyses that students of the life-sciences are being expected to perform are becoming increasingly advanced. Whether at the undergraduate, graduate, or post-graduate level, this book provides the tools needed to properly analyze your data in an efficient, accessible, plainspoken, frank, and occasionally humorous manner, ensuring that readers come away with the knowledge of which analyses they should use and when they should use them. The book uses the statistical language R, which is the choice of ecologists worldwide and is rapidly becoming the 'go-to' stats program throughout the life-sciences. Furthermore, by using a single, real-world dataset throughout the book, readers are encouraged to become deeply familiar with an imperfect but realistic set of data. Indeed, early chapters are specifically designed to teach basic data manipulation skills and build good habits in preparation for learning more advanced analyses. This approach also demonstrates the importance of viewing data through different lenses, facilitating an easy and natural progression from linear and generalized linear models through to mixed effects versions of those same analyses. Readers will also learn advanced plotting and data-wrangling techniques, and gain an introduction to writing their own functions. Applied Statistics with R is suitable for senior undergraduate and graduate students, professional researchers, and practitioners throughout the life-sciences, whether in the fields of ecology, evolution, environmental studies, or computational biology.

Download or read book Statistics and Data with R written by Yosef Cohen and published by John Wiley & Sons. This book was released on 2008-11-20 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: R, an Open Source software, has become the de facto statistical computing environment. It has an excellent collection of data manipulation and graphics capabilities. It is extensible and comes with a large number of packages that allow statistical analysis at all levels – from simple to advanced – and in numerous fields including Medicine, Genetics, Biology, Environmental Sciences, Geology, Social Sciences and much more. The software is maintained and developed by academicians and professionals and as such, is continuously evolving and up to date. Statistics and Data with R presents an accessible guide to data manipulations, statistical analysis and graphics using R. Assuming no previous knowledge of statistics or R, the book includes: A comprehensive introduction to the R language. An integrated approach to importing and preparing data for analysis, exploring and analyzing the data, and presenting results. Over 300 examples, including detailed explanations of the R scripts used throughout. Over 100 moderately large data sets from disciplines ranging from Biology, Ecology and Environmental Science to Medicine, Law, Military and Social Sciences. A parallel discussion of analyses with the normal density, proportions (binomial), counts (Poisson) and bootstrap methods. Two extensive indexes that include references to every R function (and its arguments and packages used in the book) and to every introduced concept.

Download or read book Basic and Applied Bone Biology written by David B. Burr and published by Academic Press. This book was released on 2013-06-11 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of skeletal biology from the molecular level to the organ level, including cellular control, interaction and response; adaptive responses to various external stimuli; the interaction of the skeletal system with other metabolic processes in the body; and the effect of various disease processes on the skeleton. The book also includes chapters that address how the skeleton can be evaluated through the use of various imaging technologies, biomechanical testing, histomorphometric analysis, and the use of genetically modified animal models. - Presents an in-depth overview of skeletal biology from the molecular to the organ level - Offers "refresher" level content for clinicians or researchers outside their areas of expertise - Boasts editors and many chapter authors from Indiana and Purdue Universities, two of the broadest and deepest programs in skeletal biology in the US; other chapter authors include clinician scientists from pharmaceutical companies that apply the basics of bone biology

Download or read book Applied Statistics for Environmental Science with R written by Abbas F. M. Al-Karkhi and published by Elsevier. This book was released on 2019-09-13 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Statistics for Environmental Science with R presents the theory and application of statistical techniques in environmental science and aids researchers in choosing the appropriate statistical technique for analyzing their data. Focusing on the use of univariate and multivariate statistical methods, this book acts as a step-by-step resource to facilitate understanding in the use of R statistical software for interpreting data in the field of environmental science. Researchers utilizing statistical analysis in environmental science and engineering will find this book to be essential in solving their day-to-day research problems. - Includes step-by-step tutorials to aid in understanding the process and implementation of unique data - Presents statistical theory in a simple way without complex mathematical proofs - Shows how to analyze data using R software and provides R scripts for all examples and figures

Download or read book Applied Spatial Data Analysis with R written by Roger S. Bivand and published by Springer Science & Business Media. This book was released on 2013-06-21 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Spatial Data Analysis with R, second edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS and the handling of spatio-temporal data. The second part showcases more specialised kinds of spatial data analysis, including spatial point pattern analysis, interpolation and geostatistics, areal data analysis and disease mapping. The coverage of methods of spatial data analysis ranges from standard techniques to new developments, and the examples used are largely taken from the spatial statistics literature. All the examples can be run using R contributed packages available from the CRAN website, with code and additional data sets from the book's own website. Compared to the first edition, the second edition covers the more systematic approach towards handling spatial data in R, as well as a number of important and widely used CRAN packages that have appeared since the first edition. This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data. It will also be of interest to spatial data analysts who do not use R, but who are interested in practical aspects of implementing software for spatial data analysis. It is a suitable companion book for introductory spatial statistics courses and for applied methods courses in a wide range of subjects using spatial data, including human and physical geography, geographical information science and geoinformatics, the environmental sciences, ecology, public health and disease control, economics, public administration and political science. The book has a website where complete code examples, data sets, and other support material may be found: http://www.asdar-book.org. The authors have taken part in writing and maintaining software for spatial data handling and analysis with R in concert since 2003.

Download or read book Army Research and Development written by and published by . This book was released on 1963 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Book of R written by Tilman M. Davies and published by No Starch Press. This book was released on 2016-07-16 with total page 833 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.

Download or read book Science and Technology written by Ralph Sanders and published by . This book was released on 1966 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Principles of Research Design and Drug Literature Evaluation written by Rajender R. Aparasu and published by Jones & Bartlett Publishers. This book was released on 2014-03-07 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Principles of Research Design and Drug Literature Evaluation is a unique resource that provides a balanced approach covering critical elements of clinical research, biostatistical principles, and scientific literature evaluation techniques for evidence-based medicine. This accessible text provides comprehensive course content that meets and exceeds the curriculum standards set by the Accreditation Council for Pharmacy Education (ACPE). Written by expert authors specializing in pharmacy practice and research, this valuable text will provide pharmacy students and practitioners with a thorough understanding of the principles and practices of drug literature evaluation with a strong grounding in research and biostatistical principles. Principles of Research Design and Drug Literature Evaluation is an ideal foundation for professional pharmacy students and a key resource for pharmacy residents, research fellows, practitioners, and clinical researchers. FEATURES * Chapter Pedagogy: Learning Objectives, Review Questions, References, and Online Resources * Instructor Resources: PowerPoint Presentations, Test Bank, and an Answer Key * Student Resources: a Navigate Companion Website, including Crossword Puzzles, Interactive Flash Cards, Interactive Glossary, Matching Questions, and Web Links From the Foreword: "This book was designed to provide and encourage practitioner’s development and use of critical drug information evaluation skills through a deeper understanding of the foundational principles of study design and statistical methods. Because guidance on how a study’s limited findings should not be used is rare, practitioners must understand and evaluate for themselves the veracity and implications of the inherently limited primary literature findings they use as sources of drug information to make evidence-based decisions together with their patients. The editors organized the book into three supporting sections to meet their pedagogical goals and address practitioners’ needs in translating research into practice. Thanks to the editors, authors, and content of this book, you can now be more prepared than ever before for translating research into practice." L. Douglas Ried, PhD, FAPhA Editor-in-Chief Emeritus, Journal of the American Pharmacists Association Professor and Associate Dean for Academic Affairs, College of Pharmacy, University of Texas at Tyler, Tyler, Texas

Download or read book Learning Statistics with R written by Daniel Navarro and published by Lulu.com. This book was released on 2013-01-13 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com