Modern Statistical Methods for HCI

  • Judy Robertson
  • Maurits Kaptein

Part of the Human–Computer Interaction Series book series (HCIS)

Table of contents

  1. Front Matter
    Pages i-xx
  2. Judy Robertson, Maurits Kaptein
    Pages 1-14
  3. Getting Started With Data Analysis

    1. Front Matter
      Pages 15-18
    2. Joanna Young, Jan Wessnitzer
      Pages 37-56
    3. Thom Baguley, Mark Andrews
      Pages 57-82
  4. Classical Null Hypothesis Significance Testing Done Properly

    1. Front Matter
      Pages 83-85
    2. Koji Yatani
      Pages 87-110
    3. Deborah Fry, Kerri Wazny, Niall Anderson
      Pages 111-133
    4. Jacob O. Wobbrock, Matthew Kay
      Pages 135-170
  5. Bayesian Inference

    1. Front Matter
      Pages 171-172
    2. Michail Tsikerdekis
      Pages 173-197
    3. Joris Mulder
      Pages 199-227
  6. Advanced Modeling in HCI

    1. Front Matter
      Pages 229-231
    2. A. Alexander Beaujean, Grant B. Morgan
      Pages 233-250
    3. Maurits Kaptein
      Pages 251-274
  7. Improving Statistical Practice in HCI

    1. Front Matter
      Pages 289-289
    2. Pierre Dragicevic
      Pages 291-330
    3. Judy Robertson, Maurits Kaptein
      Pages 331-348

About this book

Introduction

This book critically reflects on current statistical methods used in Human-Computer Interaction (HCI) and introduces a number of novel methods to the reader. 

Covering many techniques and approaches for exploratory data analysis including effect and power calculations, experimental design, event history analysis, non-parametric testing and Bayesian inference; the research contained in this book discusses how to communicate statistical results fairly, as well as presenting a general set of recommendations for authors and reviewers to improve the quality of statistical analysis in HCI. Each chapter presents [R] code for running analyses on HCI examples and explains how the results can be interpreted.

Modern Statistical Methods for HCI is aimed at researchers and graduate students who have some knowledge of “traditional” null hypothesis significance testing, but who wish to improve their practice by using techniques which have recently emerged from statistics and related fields. This book critically evaluates current practices within the field and supports a less rigid, procedural view of statistics in favour of fair statistical communication.


Keywords

Bayesian Analysis Experimental Design Human Computer Interaction Quantitative Analysis Research Methods and Statistics

Editors and affiliations

  • Judy Robertson
    • 1
  • Maurits Kaptein
    • 2
  1. 1.Moray School of EducationEdinburgh UniversityEdinburghUnited Kingdom
  2. 2.Donders Centre for CognitionRadboud University NijmegenTilburgThe Netherlands

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-26633-6
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-26631-2
  • Online ISBN 978-3-319-26633-6
  • Series Print ISSN 1571-5035
  • About this book
Industry Sectors
Pharma
Automotive
Electronics
Telecommunications
Consumer Packaged Goods
Aerospace