Doing Better Statistics in Human-Computer Interaction
Nonfiction, Computers, General Computing, Reference & Language, Language Arts, Reference
| Author: | Paul Cairns | ISBN: | 9781108665223 |
| Publisher: | Cambridge University Press | Publication: | February 7, 2019 |
| Imprint: | Cambridge University Press | Language: | English |
| Author: | Paul Cairns |
| ISBN: | 9781108665223 |
| Publisher: | Cambridge University Press |
| Publication: | February 7, 2019 |
| Imprint: | Cambridge University Press |
| Language: | English |
Each chapter of this book covers specific topics in statistical analysis, such as robust alternatives to t-tests or how to develop a questionnaire. They also address particular questions on these topics, which are commonly asked by human-computer interaction (HCI) researchers when planning or completing the analysis of their data. The book presents the current best practice in statistics, drawing on the state-of-the-art literature that is rarely presented in HCI. This is achieved by providing strong arguments that support good statistical analysis without relying on mathematical explanations. It additionally offers some philosophical underpinnings for statistics, so that readers can see how statistics fit with experimental design and the fundamental goal of discovering new HCI knowledge.
Each chapter of this book covers specific topics in statistical analysis, such as robust alternatives to t-tests or how to develop a questionnaire. They also address particular questions on these topics, which are commonly asked by human-computer interaction (HCI) researchers when planning or completing the analysis of their data. The book presents the current best practice in statistics, drawing on the state-of-the-art literature that is rarely presented in HCI. This is achieved by providing strong arguments that support good statistical analysis without relying on mathematical explanations. It additionally offers some philosophical underpinnings for statistics, so that readers can see how statistics fit with experimental design and the fundamental goal of discovering new HCI knowledge.
