An Introduction to Data Analysis in R: Hands-on Coding, Data Mining, Visualization and Statistics from Scratch

Description

This textbook offers an easy-to-follow, practical guide to modern data analysis using the programming language R. The chapters cover topics such as the fundamentals of programming in R, data collection and preprocessing, including web scraping, data visualization, and statistical methods, including multivariate analysis, and feature exercises at the end of each section. The text requires only basic statistics skills, as it strikes a balance between statistical and mathematical understanding and implementation in R, with a special emphasis on reproducible examples and real-world applications. This textbook is primarily intended for undergraduate students of mathematics, statistics, physics, economics, finance and business who are pursuing a career in data analytics. It will be equally valuable for master students of data science and industry professionals who want to conduct data analyses.

Get the book

Amazon.com

Search the book

eBay.com

Search the book

Similar books

• 

  Introduction to Data Science: Data Analysis and Prediction Algorithms with R

  By Rafael A. Irizarry

  This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful.

• 

  R for Data Science: Import, Tidy, Transform, Visualize, and Model Data

  By Hadley Wickham, Garrett Grolemund

  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.

• 

  Introduction to Data Science: Data Analysis and Prediction Algorithms with R

  By Rafael A. Irizarry

  Data Analysis and Prediction Algorithms with R Rafael A. Irizarry ... See Productivity tools Data analysis project organization with Unix, See Unix Data analysis project report writing, See R markdown Data analysis with large datasets, ...

• 

  Introduction to Data Analysis with R for Forensic Scientists

  By James Michael Curran

  Statistical methods provide a logical, coherent framework in which data from experimental science can be analyzed.

• 

  An Introduction to Statistical Learning: with Applications in R

  By Daniela Witten, Trevor Hastie, Robert Tibshirani

  This book presents some of the most important modeling and prediction techniques, along with relevant applications.

• 

  Doing Data Science in R: An Introduction for Social Scientists

  By Mark Andrews

  This book: Focuses on providing practical guidance for all aspects, helping readers get to grips with the tools, software, and statistical methods needed to provide the right type and level of analysis their data requires Explores the ...

• 

  Data Science for Business With R

  By Jeffrey S. Saltz, Jeffrey M. Stanton

  You can't become an expert on a topic by consulting only Wikipedia, but certainly become smarter by starting there. you can Another very useful resource is Khan Academy. Most people think of Khan Academy as a set of videos that explain ...

• 

  Data Analysis with RStudio: An Easygoing Introduction

  By Franz Kronthaler, Silke Zöllner

  ​The objective of this text is to introduce RStudio to practitioners and students and enable them to use R in their everyday work.

• 

  Introduction to Statistics and Data Analysis: With Exercises, Solutions and Applications in R

  By Christian Heumann, Michael Schomaker, Shalabh

  The text is primarily intended for undergraduate students in disciplines such as business administration, the social sciences, medicine, politics, and macroeconomics.

• 

  Data Science in Education Using R

  By Ryan A. Estrellado, Emily A. Freer, Jesse Mostipak

  —Mark Warschauer, Professor of Education and Informatics at the Universit y of California, Irvine “This book is a clear, compelling guide for real-world practitioners who are ready to use modern tools of data science in the education ...