Applied Statistics Using R
eBook - ePub

Applied Statistics Using R

A Guide for the Social Sciences

  1. 472 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Applied Statistics Using R

A Guide for the Social Sciences

About this book

If you want to learn to use R for data analysis but aren't sure how to get started, this practical book will help you find the right path through your data.

Drawing on real-world data to show you how to use different techniques in practice, it helps you progress your programming and statistics knowledge so you can apply the most appropriate tools in your research. It starts with descriptive statistics and moves through regression to advanced techniques such as structural equation modelling and Bayesian statistics, all with digestible mathematical detail for beginner researchers.

The book:

  • Shows you how to use R packages and apply functions, adjusting them to suit different datasets.
  • Gives you the tools to try new statistical techniques and empowers you to become confident using them.
  • Encourages you to learn by doing when running and adapting the authors' own code.
  • Equips you with solutions to overcome the potential challenges of working with real data that may be messy or imperfect.

Accompanied by online resources including screencast tutorials of R that give you step by step guidance and R scripts and datasets for you to practice with, this book is a perfect companion for any student of applied statistics or quantitative research methods courses.

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Yes, you can access Applied Statistics Using R by Mehmet Mehmetoglu,Matthias Mittner in PDF and/or ePUB format, as well as other popular books in Social Sciences & Social Science Research & Methodology. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Publisher Note
  4. Title Page
  5. Copyright Page
  6. Contents
  7. Online Resources
  8. About the Authors
  9. Preface
  10. 1 Introduction to R
  11. 2 Importing and Working With Data in R
  12. 3 How Does R Work?
  13. 4 Data Management
  14. 5 Data Visualization With ggplot2
  15. 6 Descriptive Statistics
  16. 7 Simple (Bivariate) Regression
  17. 8 Multiple Linear Regression
  18. 9 Dummy-Variable Regression
  19. 10 Moderation/Interaction Analysis Using Regression
  20. 11 Logistic Regression
  21. 12 Multilevel and Longitudinal Analysis
  22. 13 Factor Analysis
  23. 14 Structural Equation Modelling
  24. 15 Bayesian Statistics
  25. Bibliography
  26. Index