
Discovering Statistics Using JASP
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Discovering Statistics Using JASP
About this book
Unlock the world of statistics with Discovering Statistics using JASP, a comprehensive guide that brings the power of JASP software into the classroom. Building on the legacy of the acclaimed DSUSS series, this book distils complex statistical concepts into engaging, step-by-step content designed for undergraduate courses. Students will gain practical skills in data analysis without needing to learn coding, thanks to JASP's intuitive point-and-click interface.
This first edition also offers:
- Global relevance: Features international examples and case studies, making it ideal for diverse classroom settings.
- A student-focused approach: An abridged version tailored to undergraduate needs, with accessible summaries and practical solutions.
- Cutting-edge tools: Leverages free JASP software, supported by world-renowned experts and the University of Amsterdam.
- Alignment with open science: Encourages reproducibility and transparency in research practices.
Perfect for undergraduates and lecturers alike, this book is the ultimate resource for mastering statistics with JASP. The wealth of online resources can be easily integrated into your institution?s virtual learning environment or learning management system. This allows you to customise and curate content for use in module preparation, delivery and assessment.
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Information
Table of contents
- Cover
- Half Title
- Title Page
- Copyright Page
- Contents
- Extended Contents
- Preface
- About the Authors
- How to use this book
- Thank you
- Dedication
- Symbols used in this book
- A Brief Maths Overview
- 1 Why is my evil lecturer forcing me to learn statistics?
- 2 The SPINE of statistics
- 3 The Phoenix of statistics
- 4 The jasp of environment
- 5 Visualizing Data
- 6 The beast of bias
- 7 Correlation
- 8 The linear model (regression)
- 9 Categorical predictors: Comparing two means
- 10 Moderation and mediation
- 11 GLM 1: Comparing several independent means
- 12 GLM 2: Comparing means adjusted for other predictors (analysis of covariance)
- 13 GLM 3: Factorial designs
- 14 GLM 4: Repeated-measures designs
- 15 Non-parametric models
- 16 Categorical outcomes: chi-square
- 17 Categorical outcomes: logistic regression
- Epilogue
- Appendix
- Glossary
- References
- Index
- Acknowledgements
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