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
8 - Sorting Out Outliers
from Part II - How to Use Statistics
Published online by Cambridge University Press: 26 January 2019
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
Summary
Outliers are a problem for statistical analysis as they can have a disproportionate effect on means and statistical tests that rely on means. This chapter looks first at how to identify outliers and then, from thinking about what might cause an outlier, how best to analyse data when there are outliers.
- Type
- Chapter
- Information
- Doing Better Statistics in Human-Computer Interaction , pp. 95 - 103Publisher: Cambridge University PressPrint publication year: 2019