| 000 | 03329cam a2200469M 4500 | ||
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| 001 | 9780367409913 | ||
| 003 | FlBoTFG | ||
| 005 | 20220509192943.0 | ||
| 006 | m o d | ||
| 007 | cr |n||||||||| | ||
| 008 | 200103s2019 xx o 000 0 eng d | ||
| 040 |
_aOCoLC-P _beng _cOCoLC-P |
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| 020 |
_a9781000763461 _q(electronic bk.) |
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| 020 |
_a1000763463 _q(electronic bk.) |
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| 020 |
_a9780367409913 _q(electronic bk.) |
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_a0367409917 _q(electronic bk.) |
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| 020 |
_a9781000763560 _q(electronic bk. : EPUB) |
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| 020 |
_a1000763560 _q(electronic bk. : EPUB) |
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| 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 |
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