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Autor(en): 
  • Chester Ismay
  • Albert Y Kim
  • Statistical Inference via Data Science: A ModernDive into R and the Tidyverse 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Dezember 2019  
    Genre:  Schulbücher 
     
    BUSINESS & ECONOMICS / Statistics / COMPUTERS / Data Processing / COMPUTERS / Optical Data Processing / COMPUTERS / Programming Languages / C / Mathematics / MATHEMATICS / Probability & Statistics / Regression Analysis
    ISBN:  9780367409876 
    EAN-Code: 
    9780367409876 
    Verlag:  Taylor & Francis Ltd (Sales) 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  Chapman & Hall/CRC The R Series  
    Dimensionen:  H 260 mm / B 183 mm / D 29 mm 
    Gewicht:  1057 gr 
    Seiten:  430 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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.

      



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