
- 376 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
Understanding Quantitative Data in Educational Research
About this book
This book is designed to help you gain confidence in analysing and interpreting quantitative data and using appropriate statistical tests, by exploring, in plain language, a variety of data analysis methods.
Highly practical, each chapter includes step-by-step instructions on how to run specific statistical tests using R, practical tips on how to interpret results correctly and exercises to put into practice what you have learned.
It also includes guidance on how to use R and RStudio, how to visualise quantitative data, and the fundamentals of inferential statistics, estimations and hypothesis testing.
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Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Yes, you can access Understanding Quantitative Data in Educational Research by Nicoleta Gaciu,Author in PDF and/or ePUB format, as well as other popular books in Education & Research in Education. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Cover
- Half Title
- Publisher Note
- Title Page
- Copyright Page
- Acknowledgements
- Contents
- About the author
- About the online resources
- Acknowledgements
- Introduction
- Part One Understanding quantitative data and R
- 1 Introduction to information, knowledge and quantitative data
- 2 An introduction to R and RStudio
- Part Two Data visualisation
- 3 Graphical representation of data
- Part Three Providing information about data
- 4 Descriptive statistics
- 5 Measures of dispersion and distributions
- 6 Normal distribution and standardised scores
- Part Four Making estimations and predictions from data
- 7 Fundamentals of inferential statistics
- 8 Estimation and hypothesis testing
- Part Five From sample to population
- 9 One-sample tests
- 10 Differences between two independent or dependent samples
- 11 Differences between more than two independent samples
- 12 Differences between more than two dependent samples
- Part Six Relationships and predictions
- 13 Relationships between variables
- 14 Predictions for independent and dependent variables
- Bibliography
- Index