391,49 €
434,99 €
-10% with code: EXTRA
Project-Based R Companion to Introductory Statistics
Project-Based R Companion to Introductory Statistics
391,49
434,99 €
  • We will send in 10–14 business days.
Project-Based R Companion to Introductory Statistics is envisioned as a companion to a traditional statistics or biostatistics textbook, with each chapter covering traditional topics such as descriptive statistics, regression, and hypothesis testing. However, unlike a traditional textbook, each chapter will present its material using a complete step-by-step analysis of a real publicly available dataset, with an emphasis on the practical skills of testing assumptions, data exploration, and formi…
  • Publisher:
  • ISBN-10: 0367687348
  • ISBN-13: 9780367687342
  • Format: 15.5 x 23.1 x 1.5 cm, hardcover
  • Language: English
  • SAVE -10% with code: EXTRA

Project-Based R Companion to Introductory Statistics (e-book) (used book) | bookbook.eu

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Description

Project-Based R Companion to Introductory Statistics is envisioned as a companion to a traditional statistics or biostatistics textbook, with each chapter covering traditional topics such as descriptive statistics, regression, and hypothesis testing. However, unlike a traditional textbook, each chapter will present its material using a complete step-by-step analysis of a real publicly available dataset, with an emphasis on the practical skills of testing assumptions, data exploration, and forming conclusions. The chapters in the main body of the book include a worked example showing the R code used at each step followed by a multi-part project for students to complete. These projects, which could serve as alternatives to traditional discrete homework problems, will illustrate how to "put the pieces together" and conduct a complete start-to-finish data analysis using the R statistical software package. At the end of the book, there are several projects that require the use of multiple statistical techniques that could be used as a take-home final exam or final project for a class.

Key features of the text:

  • Organized in chapters focusing on the same topics found in typical introductory statistics textbooks (descriptive statistics, regression, two-way tables, hypothesis testing for means and proportions, etc.) so instructors can easily pair this supplementary material with course plans

  • Includes student projects for each chapter which can be assigned as laboratory exercises or homework assignments to supplement traditional homework

  • Features real-world datasets from scientific publications in the fields of history, pop culture, business, medicine, and forensics for students to analyze

  • Allows students to gain experience working through a variety of statistical analyses from start to finish

The book is written at the undergraduate level to be used in an introductory statistical methods course or subject-specific research methods course such as biostatistics or research methods for psychology or business analytics.

Author

After a 10-year career as a research biostatistician in the Department of Ophthalmology and Visual Sciences at the University of Wisconsin-Madison, Chelsea Myers teaches statistics and biostatistics at Rollins College and Valencia College in Central Florida. She has authored or co-authored more than 30 scientific papers and presentations and is the creator of the MCAT preparation website MCATMath.com.

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  • Author: Chelsea Myers
  • Publisher:
  • ISBN-10: 0367687348
  • ISBN-13: 9780367687342
  • Format: 15.5 x 23.1 x 1.5 cm, hardcover
  • Language: English English

Project-Based R Companion to Introductory Statistics is envisioned as a companion to a traditional statistics or biostatistics textbook, with each chapter covering traditional topics such as descriptive statistics, regression, and hypothesis testing. However, unlike a traditional textbook, each chapter will present its material using a complete step-by-step analysis of a real publicly available dataset, with an emphasis on the practical skills of testing assumptions, data exploration, and forming conclusions. The chapters in the main body of the book include a worked example showing the R code used at each step followed by a multi-part project for students to complete. These projects, which could serve as alternatives to traditional discrete homework problems, will illustrate how to "put the pieces together" and conduct a complete start-to-finish data analysis using the R statistical software package. At the end of the book, there are several projects that require the use of multiple statistical techniques that could be used as a take-home final exam or final project for a class.

Key features of the text:

  • Organized in chapters focusing on the same topics found in typical introductory statistics textbooks (descriptive statistics, regression, two-way tables, hypothesis testing for means and proportions, etc.) so instructors can easily pair this supplementary material with course plans

  • Includes student projects for each chapter which can be assigned as laboratory exercises or homework assignments to supplement traditional homework

  • Features real-world datasets from scientific publications in the fields of history, pop culture, business, medicine, and forensics for students to analyze

  • Allows students to gain experience working through a variety of statistical analyses from start to finish

The book is written at the undergraduate level to be used in an introductory statistical methods course or subject-specific research methods course such as biostatistics or research methods for psychology or business analytics.

Author

After a 10-year career as a research biostatistician in the Department of Ophthalmology and Visual Sciences at the University of Wisconsin-Madison, Chelsea Myers teaches statistics and biostatistics at Rollins College and Valencia College in Central Florida. She has authored or co-authored more than 30 scientific papers and presentations and is the creator of the MCAT preparation website MCATMath.com.

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