Data Analysis With R
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Beginner's Guide for Data Analysis using R Programming
R programming is an efficient tool for statistical analysis of data. Data science has become critical to each field and the popularity of R is skyrocketing. Organization as large and diverse as Google, Facebook, Microsoft, Bank of America, Ford Motor Company, Mozilla, Thomas Cook, The New York Times, The National Weather Service, Twitter, ANZ Bank, Uber, Airbnb etc . have turned to R for reporting, analyzing and visualization of data, this book is for students and professionals of Mathematics, Statistics, Physics, Chemistry, Biology, Social Science and Medicine, Business, Engineering, Software, Information Technology, Sales, Bio Informatics, Pharmacy and any one, where data needs to be analyzed and represented graphically.
R Programming for Data Analysis
Unlock the Power of Data with R Programming for Data Analysis — Your Complete Guide from Beginner to Expert! Are you eager to master data analytics using R programming but unsure where to start? Whether you're a student, aspiring data analyst, or professional looking to upskill, this book is the perfect starting point to learn R for data analysis and become proficient with one of the most powerful tools in the industry. What Makes This Book Your Ultimate Resource for Data Analysis Using R Software? This comprehensive guide covers everything you need to confidently use R software data analysis tools, starting from installation to mastering essential programming concepts. You’ll learn how to harness the full potential of the R language for data science and data analytics with R programming to unlock actionable insights from your data. Inside You’ll Discover: Step-by-step guidance on setting up R and RStudio, the leading R data analysis software, so you can get started quickly. Master core data structures in R language data analysis: vectors, lists, data frames, and factors—building blocks for efficient data analysis using R programming. Practical techniques for cleaning, transforming, and visualizing data—skills every R data analyst needs. How to apply data science with R basics to perform statistical analysis and modeling. Real-world examples that make learning intuitive and effective—like a top R programming course or R programming training session. Who Should Read This? Beginners wanting to learn R programming specifically for data science with R Analysts seeking to upgrade their skills using the best r analysis software Students enrolled in a data science with R course or anyone learning the r programming language course Professionals eager to master r coding language for actionable data analytics R programming Why Choose This Book Over Others? This isn’t just another technical manual. It’s designed to simplify the complexities of R programming for data analysis with clear explanations, practical exercises, and a focus on real-world applications. Whether you want to become a skilled R language for data analytics professional or simply want to understand your data better, this book makes it achievable. Start your journey to becoming a confident data analyst today. Scroll up and order R Programming for Data Analysis now—unlock insights, drive decisions, and transform data into success!
Data Analysis with R
Author: Tony Fischetti
language: en
Publisher: Packt Publishing Ltd
Release Date: 2015-12-22
Load, wrangle, and analyze your data using the world's most powerful statistical programming language About This Book Load, manipulate and analyze data from different sources Gain a deeper understanding of fundamentals of applied statistics A practical guide to performing data analysis in practice Who This Book Is For Whether you are learning data analysis for the first time, or you want to deepen the understanding you already have, this book will prove to an invaluable resource. If you are looking for a book to bring you all the way through the fundamentals to the application of advanced and effective analytics methodologies, and have some prior programming experience and a mathematical background, then this is for you. What You Will Learn Navigate the R environment Describe and visualize the behavior of data and relationships between data Gain a thorough understanding of statistical reasoning and sampling Employ hypothesis tests to draw inferences from your data Learn Bayesian methods for estimating parameters Perform regression to predict continuous variables Apply powerful classification methods to predict categorical data Handle missing data gracefully using multiple imputation Identify and manage problematic data points Employ parallelization and Rcpp to scale your analyses to larger data Put best practices into effect to make your job easier and facilitate reproducibility In Detail Frequently the tool of choice for academics, R has spread deep into the private sector and can be found in the production pipelines at some of the most advanced and successful enterprises. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. With over 7,000 user contributed packages, it's easy to find support for the latest and greatest algorithms and techniques. Starting with the basics of R and statistical reasoning, Data Analysis with R dives into advanced predictive analytics, showing how to apply those techniques to real-world data though with real-world examples. Packed with engaging problems and exercises, this book begins with a review of R and its syntax. From there, get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. Solve the difficulties relating to performing data analysis in practice and find solutions to working with “messy data”, large data, communicating results, and facilitating reproducibility. This book is engineered to be an invaluable resource through many stages of anyone's career as a data analyst. Style and approach Learn data analysis using engaging examples and fun exercises, and with a gentle and friendly but comprehensive "learn-by-doing" approach.