Statistical Inference via Data Science A ModernDive into R and the Tidyverse - Info and Reading Options
By Chester Ismay and Albert Y. Kim
"Statistical Inference via Data Science A ModernDive into R and the Tidyverse" was published by CRC Press in 2020 - Boca Raton, it has 460 pages and the language of the book is English.
“Statistical Inference via Data Science A ModernDive into R and the Tidyverse” Metadata:
- Title: ➤ Statistical Inference via Data Science A ModernDive into R and the Tidyverse
- Authors: Chester IsmayAlbert Y. Kim
- Language: English
- Number of Pages: 460
- Publisher: CRC Press
- Publish Date: 2020
- Publish Location: Boca Raton
“Statistical Inference via Data Science A ModernDive into R and the Tidyverse” Subjects and Themes:
- Subjects: ➤ Mathematical statistics - Linear models - Analysis of variance - Regression analysis - Estimation theory - Statistics, data processing - Statistics - Data processing - Quantitative research - R (Computer program language) - MATHEMATICS / Probability & Statistics / Regression Analysis - MATHEMATICS - Probability & Statistics - Regression Analysis
Edition Specifications:
- Format: Hardcover
- Weight: 2 pounds
Edition Identifiers:
- The Open Library ID: OL27923192M - OL20650147W
- Online Computer Library Center (OCLC) ID: 1151748127 - 1122721598
- Library of Congress Control Number (LCCN): 2019042573
- ISBN-13: 9780367409821 - 9780367409913
- ISBN-10: 0367409828
- All ISBNs: 0367409828 - 9780367409821 - 9780367409913
AI-generated Review of “Statistical Inference via Data Science A ModernDive into R and the Tidyverse”:
"Statistical Inference via Data Science A ModernDive into R and the Tidyverse" Description:
Open Data:
"Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference using data science tools widely used in industry, academia, and government. It introduces the tidyverse suite of R packages, including the ggplot2 package for data visualization, and the dplyr package for data wrangling. After equipping readers with just enough of these data science tools to perform effective exploratory data analyses, the book covers traditional introductory statistics topics like confidence intervals, hypothesis testing, and multiple regression modeling, while focusing on visualization throughout"--
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