Details

Title Modern Statistical Methods for HCI (Human-Computer Interaction Series)
Author Robertson, Judy
Binding Paperback
Edition Softcover reprint of the original 1st ed. 2016
Condition New
Pages 348
Volumes 1
Language ENG
Publisher Springer
Publication date 2018-04-24
Illustrated Yes
Features Illustrated
Bookseller's Inventory # DADAX3319799843
ISBN 9783319799841 / 3319799843
Weight 1.14 lbs (0.52 kg)
Dimensions 9.21 x 6.14 x 0.77 in (23.39 x 15.60 x 1.96 cm)
Size 6.10x0.83x9.25
Category Computers - General Information
Dewey Decimal Code 005.437
Quantity available 1

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From the publisher

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 relatedfields. This book critically evaluates current practices within the field and supports a less rigid, procedural view of statistics in favour of fair statistical communication.

From the rear cover

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.

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