Tony Fischetti Data Analysis with R

ISBN 13: 9781785288142

Data Analysis with R

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9781785288142: Data Analysis with R
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Key Features

  • 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
Book DescriptionFrequently 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.
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
Table of Contents
  1. RefresheR
  2. The Shape of Data
  3. Describing Relationships
  4. Probability
  5. Using Data to Reason About the World
  6. Testing Hypotheses
  7. Bayesian Methods
  8. Predicting Continuous Variables
  9. Predicting Categorical Variables
  10. Sources of Data
  11. Dealing with Messy Data
  12. Dealing with Large Data
  13. Reproducibility and Best Practices

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About the Author:

Tony Fischetti is a data scientist at the NewYork Public Library, where he uses R everyday. He graduated in cognitive and computer science from Rensselaer Polytechnic Institute. His thesiswas strongly focused on using statistics to study visual short-termmemory.

He enjoys writing and contributing to open sourcesoftware, blogging at "On The Lambda", writing about himself in thethird person, and sharing knowledge using simple, approachable languageand engaging examples.

"About this title" may belong to another edition of this title.

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Tony Fischetti
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Book Description Packt Publishing Limited, United Kingdom, 2015. Paperback. Condition: New. Language: English . Brand New Book ***** Print on Demand *****.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. Seller Inventory # AAV9781785288142

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Book Description Packt Publishing Limited, United Kingdom, 2015. Paperback. Condition: New. Language: English . Brand New Book ***** Print on Demand *****. 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. Seller Inventory # AAV9781785288142

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Book Description Packt Publishing - ebooks Account. Paperback. Condition: New. 446 pages. Dimensions: 9.2in. x 7.5in. x 0.8in.Load, wrangle, and analyze your data using the worlds most powerful statistical programming languageAbout This BookLoad, manipulate and analyze data from different sourcesGain a deeper understanding of fundamentals of applied statisticsA practical guide to performing data analysis in practiceWho This Book Is ForWhether 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 LearnNavigate the R environmentDescribe and visualize the behavior of data and relationships between dataGain a thorough understanding of statistical reasoning and samplingEmploy hypothesis tests to draw inferences from your dataLearn Bayesian methods for estimating parametersPerform regression to predict continuous variablesApply powerful classification methods to predict categorical dataHandle missing data gracefully using multiple imputationIdentify and manage problematic data pointsEmploy parallelization and Rcpp to scale your analyses to larger dataPut best practices into effect to make your job easier and facilitate reproducibilityIn DetailFrequently 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, its 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 anyones career as a data analyst. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Paperback. Seller Inventory # 9781785288142

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