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
9 - Power and Two Types of Error
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
The focus of statistical testing on significance can lead to the two types of error discussed in this chapter: finding a significant result when there is no underlying real effect; failing to get significance when there is in fact an underlying real effect. Though a blinkered approach to significance can be problematic for good data analysis, consideration of the two types of error is useful first to help think about sample sizes in studies but, second, it is a good way to assess the quality and robustness of statistical tests.
- Type
- Chapter
- Information
- Doing Better Statistics in Human-Computer Interaction , pp. 104 - 113Publisher: Cambridge University PressPrint publication year: 2019