Modern Statistical Methods for HCI / edited by Judy Robertson, Maurits Kaptein.

Format:

Book

Contributor:

Robertson, Judy (Computer scientist), editor.

Kaptein, Maurits, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Human-computer interaction series 1571-5035

Human-Computer Interaction Series, 1571-5035

Language:

English

Subjects (All):

User interfaces (Computer systems).

Statistics.

User Interfaces and Human Computer Interaction.

Statistics for Social Sciences, Humanities, Law.

Local Subjects:

User Interfaces and Human Computer Interaction.

Statistics for Social Sciences, Humanities, Law.

Physical Description:

1 online resource (XX, 348 pages) : 77 illustrations.

Edition:

First edition 2016.

Contained In:

Springer eBooks

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2016.

System Details:

text file PDF

Summary:

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.

Contents:

Preface

An Introduction to Modern Statistical Methods for HCI

Part I: Getting Started With Data Analysis

Getting started with [R]: A Brief Introduction

Descriptive Statistics, Graphs, and Visualization

Handling Missing Data

Part II: Classical Null Hypothesis Significance Testing Done Properly

Effect sizes and Power in HCI

Using R for Repeated and Time-Series Observations

Non-Parametric Statistics in Human-Computer Interaction

Part III : Bayesian Inference

Bayesian Inference

Bayesian Testing of Constrained Hypothesis

Part IV: Advanced Modeling in HCI

Latent Variable Models

Using Generalized Linear (Mixed) Models in HCI

Mixture Models: Latent Profile and Latent Class Analysis

Part V: Improving Statistical Practice in HCI

Fair Statistical Communication in HCI

Improving Statistical Practice in HCI.

Other Format:

Printed edition:

ISBN:

978-3-319-26633-6

9783319266336

Access Restriction:

Restricted for use by site license.