R Companion to Elementary Applied Statistics

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beginner guide to R statistical computing
Bivariate Normal Sample
Bivariate Normality Assumption
Blacktail Deer
categorical data
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Confidence Interval Error Bars
Constant Variances Assumption
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CSV File
Cumulative Distribution Function
Data Frame
Data In R
data visualization tools
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Dot Chart
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Fligner Killeen Test
Graphics Parameter Settings
Grouped Frequency Distribution
hypothesis testing techniques
inferential statistics concepts
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Left Tailed Probability
Normal Approximation Approaches
Normal Approximation Points
Normal Approximation Test
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parametric and nonparametric tests
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quantitative research methods
R Graphics
R Packages
Sapply Function
Script File
Smallest Quantile
softlaunch
statistical computing
statistical data analysis
Studentized Maximum Modulus Distribution
Studentized Range Distribution
Tapply Function
Underlying Random Variables
Unequal Variances Case
Vice Versa

Product details

  • ISBN 9781138329164
  • Weight: 560g
  • Dimensions: 156 x 234mm
  • Publication Date: 08 Jan 2019
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
  • Language: English
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The R Companion to Elementary Applied Statistics includes traditional applications covered in elementary statistics courses as well as some additional methods that address questions that might arise during or after the application of commonly used methods. Beginning with basic tasks and computations with R, readers are then guided through ways to bring data into R, manipulate the data as needed, perform common statistical computations and elementary exploratory data analysis tasks, prepare customized graphics, and take advantage of R for a wide range of methods that find use in many elementary applications of statistics.

Features:

  • Requires no familiarity with R or programming to begin using this book.
  • Can be used as a resource for a project-based elementary applied statistics course, or for researchers and professionals who wish to delve more deeply into R.
  • Contains an extensive array of examples that illustrate ideas on various ways to use pre-packaged routines, as well as on developing individualized code.
  • Presents quite a few methods that may be considered non-traditional, or advanced.
  • Includes accompanying carefully documented script files that contain code for all examples presented, and more.

R is a powerful and free product that is gaining popularity across the scientific community in both the professional and academic arenas. Statistical methods discussed in this book are used to introduce the fundamentals of using R functions and provide ideas for developing further skills in writing R code. These ideas are illustrated through an extensive collection of examples.


About the Author:


Christopher Hay-Jahans

received his Doctor of Arts in mathematics from Idaho State University in 1999. After spending three years at University of South Dakota, he moved to Juneau, Alaska, in 2002 where he has taught a wide range of undergraduate courses at University of Alaska Southeast.

Christopher Hay-Jahans received his Doctor of Arts in mathematics from Idaho State University in 1999. After spending three years at University of South Dakota, he moved to Juneau, Alaska, in 2002 where he has taught a wide range of undergraduate courses at University of Alaska Southeast.

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