
- 448 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
About this book
Statistics is made simple with this award-winning guide to using R and applied statistical methods. With a clear step-by-step approach explained using real world examples, learn the practical skills you need to use statistical methods in your research from an expert with over 30 years of teaching experience. With a wealth of hands-on exercises and online resources created by the author, practice your skills using the data sets and R scripts from the book with detailed screencasts that accompany each script. This book is ideal for anyone looking to:
â˘Complete an introductory course in statistics
â˘Prepare for more advanced statistical courses
â˘Gain the transferable analytical skills needed to interpret research from across the social sciences
â˘Learn the technical skills needed to present data visually
â˘Acquire a basic competence in the use of R and RStudio. This edition also includes a gentle introduction to Bayesian methods integrated throughout. The author has created a wide range of online resources, including: over 90 R scripts, 36 datasets, 37 screen casts, complete solutions for all exercises, and 130 multiple-choice questions to test your knowledge.
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Information
Table of contents
- Cover
- Half Title
- Publisher Note
- Title Page
- Copyright Page
- Acknowledgements
- Contents
- About the Author
- Preface to the Second Edition
- Discover this Textbookâs Online Resources!
- Acknowledgments
- 1 Introduction and R Instructions
- 2 Descriptive Statistics: Tabular and Graphical Methods
- 3 Descriptive Statistics: Numerical Methods
- 4 Introduction to Probability
- 5 Discrete Probability Distributions
- 6 Continuous Probability Distributions
- 7 Point Estimation and Sampling Distributions
- 8 Confidence Interval Estimation
- 9 Hypothesis Tests: Introduction, Basic Concepts, and an Example
- 10 Hypothesis Tests about Means and Proportions: Applications
- 11 Comparisons of Means and Proportions
- 12 Simple Linear Regression
- 13 Multiple Regression