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001 9780367409913
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006 m o d
007 cr |n|||||||||
008 200103s2019 xx o 000 0 eng d
040 _aOCoLC-P
_beng
_cOCoLC-P
020 _a9781000763461
_q(electronic bk.)
020 _a1000763463
_q(electronic bk.)
020 _a9780367409913
_q(electronic bk.)
020 _a0367409917
_q(electronic bk.)
020 _a9781000763560
_q(electronic bk. : EPUB)
020 _a1000763560
_q(electronic bk. : EPUB)
020 _z0367409879
020 _z9780367409876
020 _z9780367409821
020 _z0367409828
035 _a(OCoLC)1134514261
035 _a(OCoLC-P)1134514261
050 4 _aQA276.45.R3
072 7 _aMAT
_x029030
_2bisacsh
072 7 _aPBT
_2bicssc
082 0 4 _a519.5/4
_223
100 1 _aIsmay, Chester.
245 1 0 _aSTATISTICAL INFERENCE VIA DATA SCIENCE
_h[electronic resource] :
_ba moderndive into R and the Tidyverse.
260 _a[S.l.] :
_bCRC PRESS,
_c2019.
300 _a1 online resource.
490 1 _aChapman & Hall/CRC the R series
520 _aStatistical 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.
588 _aOCLC-licensed vendor bibliographic record.
650 7 _aMATHEMATICS / Probability & Statistics / Regression Analysis
_2bisacsh
650 0 _aStatistics
_xData processing.
650 0 _aQuantitative research.
650 0 _aR (Computer program language)
700 1 _aKim, Albert Young-Sun,
_d1980-
856 4 0 _3Taylor & Francis
_uhttps://www.taylorfrancis.com/books/9780367409913
856 4 2 _3OCLC metadata license agreement
_uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
999 _c127172
_d127172