03364cam a2200481M 4500 9780367409913 FlBoTFG 20260210180730.0 m o d cr |n||||||||| 200103s2019 xx o 000 0 eng d OCoLC-P eng OCoLC-P 9781000763461 (electronic bk.) 1000763463 (electronic bk.) 9780367409913 (electronic bk.) 0367409917 (electronic bk.) 9781000763560 (electronic bk. : EPUB) 1000763560 (electronic bk. : EPUB) 0367409879 9780367409876 9780367409821 0367409828 (OCoLC)1134514261 (OCoLC-P)1134514261 QA276.45.R3 MAT 029030 bisacsh PBT bicssc 519.5/4 23 Ismay, Chester. STATISTICAL INFERENCE VIA DATA SCIENCE [electronic resource] : a moderndive into R and the Tidyverse. [S.l.] : CRC PRESS, 2019. 1 online resource. Chapman & Hall/CRC the R series 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. Features: Assumes minimal prerequisites, notably, no prior calculus nor coding experience Motivates theory using real-world data, including all domestic flights leaving New York City in 2013, the Gapminder project, and the data journalism website, FiveThirtyEight.com Centers on simulation-based approaches to statistical inference rather than mathematical formulas Uses the infer package for "tidy" and transparent statistical inference to construct confidence intervals and conduct hypothesis tests via the bootstrap and permutation methods Provides all code and output embedded directly in the text; also available in the online version at moderndive.com This book is intended for individuals who would like to simultaneously start developing their data science toolbox and start learning about the inferential and modeling tools used in much of modern-day research. The book can be used in methods and data science courses and first courses in statistics, at both the undergraduate and graduate levels. OCLC-licensed vendor bibliographic record. MATHEMATICS / Probability & Statistics / Regression Analysis bisacsh Statistics Data processing. 5075 Quantitative research. R (Computer program language) Kim, Albert Young-Sun, 1980- Taylor & Francis https://www.taylorfrancis.com/books/9780367409913 OCLC metadata license agreement http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf 89721 89720