Book contents
- Frontmatter
- Dedication
- Contents
- Figures
- Tables
- Acknowledgements
- Getting Started
- Part I Why We Use Statistics
- Part II How to Use Statistics
- 5 Planning Your Statistical Analysis
- 6 A Cautionary Tail: Why You Should Not Do a One-Tailed Test
- 7 Is This Normal?
- 8 Sorting Out Outliers
- 9 Power and Two Types of Error
- 10 Using Non-Parametric Tests
- 11 A Robust t-Test
- 12 The ANOVA Family and Friends
- 13 Exploring, Over-Testing and Fishing
- 14 When Is a Correlation Not a Correlation?
- 15 What Makes a Good Likert Item?
- 16 The Meaning of Factors
- 17 Unreliable Reliability: The Problem of Cronbach’s Alpha
- 18 Tests for Questionnaires
- Index
10 - Using Non-Parametric Tests
from Part II - How to Use Statistics
Published online by Cambridge University Press: 26 January 2019
- Frontmatter
- Dedication
- Contents
- Figures
- Tables
- Acknowledgements
- Getting Started
- Part I Why We Use Statistics
- Part II How to Use Statistics
- 5 Planning Your Statistical Analysis
- 6 A Cautionary Tail: Why You Should Not Do a One-Tailed Test
- 7 Is This Normal?
- 8 Sorting Out Outliers
- 9 Power and Two Types of Error
- 10 Using Non-Parametric Tests
- 11 A Robust t-Test
- 12 The ANOVA Family and Friends
- 13 Exploring, Over-Testing and Fishing
- 14 When Is a Correlation Not a Correlation?
- 15 What Makes a Good Likert Item?
- 16 The Meaning of Factors
- 17 Unreliable Reliability: The Problem of Cronbach’s Alpha
- 18 Tests for Questionnaires
- Index
Summary
Non-parametric tests, in particular rank-based tests, are often proposed as robust alternatives to parametric tests like t-tests when the assumptions of parametric tests are violated. However, non-parametric tests have their own assumptions which, when not considered, can lead to misinterpretation and unsound conclusions based on those tests. This chapter explores these problems and differentiates between the more and less robust non-parametric tests. Modern robust alternative non-parametric tests are suggested to replace the less robust tests.
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- Doing Better Statistics in Human-Computer Interaction , pp. 114 - 124Publisher: Cambridge University PressPrint publication year: 2019