Modern Data Science with R

The increasing volume and sophistication of data poses new challenges for analysts, who need to be able to transform complex data sets to answer important statistical questions. A consensus report on data science for undergraduates ...

Modern Data Science with R

From a review of the first edition: "Modern Data Science with R... is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician). Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions. The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice.

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Modern Data Science with R
Language: en
Pages: 650
Authors: Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton
Categories: Business & Economics
Type: BOOK - Published: 2021-04-13 - Publisher: CRC Press

From a review of the first edition: "Modern Data Science with R... is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician). Modern
Modern Data Science with R
Language: en
Pages: 551
Authors: Benjamin Baumer, Daniel Kaplan, Nicholas J. Horton
Categories: Big data
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Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world problems with data. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged
Data Science with R for Psychologists and Healthcare Professionals
Language: en
Pages: 312
Authors: Christian Ryan
Categories: Business & Economics
Type: BOOK - Published: 2021-12-23 - Publisher: CRC Press

This introduction to R for students of psychology and health sciences aims to fast-track the reader through some of the most difficult aspects of learning to do data analysis and statistics. It demonstrates the benefits for reproducibility and reliability of using a programming language over commercial software packages such as
Foundations of Statistics for Data Scientists
Language: en
Pages: 486
Authors: Alan Agresti, Maria Kateri
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Type: BOOK - Published: 2021-11-22 - Publisher: CRC Press

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Analyzing Baseball Data with R, Second Edition
Language: en
Pages: 342
Authors: Max Marchi, Jim Albert, Benjamin S. Baumer
Categories: Mathematics
Type: BOOK - Published: 2018-11-19 - Publisher: CRC Press

Analyzing Baseball Data with R Second Edition introduces R to sabermetricians, baseball enthusiasts, and students interested in exploring the richness of baseball data. It equips you with the necessary skills and software tools to perform all the analysis steps, from importing the data to transforming them into an appropriate format