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Statistics with R
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Statistics with R
A Beginner's Guide

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January 2018 | 384 pages | SAGE Publications Ltd
The dynamic, student focused textbook provides step-by-step instruction in the use of R and of statistical language as a general research tool. It is ideal for readers hoping to:
  • Complete an introductory course in statistics
  • Prepare for more advanced statistical courses
  • Gain the transferable analytical skills needed to interpret research from across the social sciences
  • Learn the technical skills needed to present data visually
  • Acquire a basic competence in the use of R
Statistics with R provides readers with the conceptual foundation to use applied statistical methods in everyday research. Each statistical method is developed within the context of practical, real-world examples and is supported by carefully developed pedagogy and jargon-free definitions. Theory is introduced as an accessible and adaptable tool and is always contextualized within the pragmatic context of real research projects and definable research questions.
 
Chapter 1: Introduction and R Instructions
 
Chapter 2: Descriptive Statistics: Tabular and Graphical Methods
 
Chapter 3: Descriptive Statistics: Numerical Methods
 
Chapter 4: Introduction to Probability
 
Chapter 5: Discrete Probability Distributions
 
Chapter 6: Continuous Probability Distributions
 
Chapter 7: Point Estimation and Sampling Distributions
 
Chapter 8: Confidence Interval Estimation
 
Chapter 9: Hypothesis Tests: Introduction, Basic Concepts, and an Example
 
Chapter 10: Hypothesis Tests About u and p: Applications
 
Chapter 11: Comparisons of Means and Proportions
 
Chapter 12: Simple Linear Regression
 
Chapter 13: Multiple Regression

Robert Stinerock provides a much-needed, easy-to-follow introduction to statistics and the R programming language. Any reader wishing to master and implement the statistical methods needed to derive meaning from data in today’s challenging information-rich environment will benefit from this insightful, exciting, and profoundly useful text.

Morris B. Holbrook
W. T. Dillard Professor Emeritus of Marketing, Columbia University

The ability to code, analyze, and derive insights from vast amounts of data are critical skills in today’s world of big data. This well-written book provides an excellent introduction to statistics and R programming language.

Sunil Gupta
Edward W. Carter Professor of Business, Harvard Business School

The book provides an excellent guide to statistics and the R programming language for beginners. Its wide range is exceptional to meet readers' needs in the era of big data and data science being the future. Brilliant!

Shaomin Wu
Reader in Business/Applied Statistics, University of Kent
Key features
KEY FEATURES:
  • In-depth R tutorials that start from the act of locating and downloading the software and continue through each statistical method
  • Shows readers how to use R in a gradual way that builds confidence and eliminates fear
  • Grounds each statistical method in practical, real world examples that are both timely and interdisciplinary
  • Provides carefully cultivated, jargon-free pedagogy that appeals to different learning styles through a mix of text, visuals, and off the page learning
  • Provides readers with a step-by-step guide to statistical language that includes a variety of resources for reflection, revision, and practice
 

  • Through in-depth R tutorials that start from the act of locating and downloading the software and continue through each statistical method, this book shows students how to use R in a gradual way that builds confidence and eliminates fear, as the software becomes more prevalent on undergraduate and introductory statistics courses.
  • By grounding each statistical method in practical, real world examples that are both timely and interdisciplinary students can see how to overcome their struggles with conceptualizing how to apply statistical knowledge outside of the exams and classroom activities
  • For students who lack confidence in their statistical literacy and get easily frustrated with challenging concepts, the text provides carefully cultivated, jargon-free pedagogy that appeals to different learning styles through a mix of text, visuals and off the page learning.
  • Provides students with a step-by-step guide to statistical language that includes a variety of resources for reflection, revision and practice to ensure students retain and maintain knowledge of key concepts through learning exercises, data sets, formulae lists, accessible definitions, and software screenshots

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    ISBN: 9781473924901
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