000 03796nam a22005175i 4500
001 978-3-319-26633-6
003 DE-He213
005 20200421111652.0
007 cr nn 008mamaa
008 160322s2016 gw | s |||| 0|eng d
020 _a9783319266336
_9978-3-319-26633-6
024 7 _a10.1007/978-3-319-26633-6
_2doi
050 4 _aQA76.9.U83
050 4 _aQA76.9.H85
072 7 _aUYZG
_2bicssc
072 7 _aCOM070000
_2bisacsh
082 0 4 _a005.437
_223
082 0 4 _a4.019
_223
245 1 0 _aModern Statistical Methods for HCI
_h[electronic resource] /
_cedited by Judy Robertson, Maurits Kaptein.
250 _a1st ed. 2016.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXX, 348 p. 77 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aHuman-Computer Interaction Series,
_x1571-5035
505 0 _aPreface -- 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.
520 _aThis 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.
650 0 _aComputer science.
650 0 _aUser interfaces (Computer systems).
650 0 _aStatistics.
650 1 4 _aComputer Science.
650 2 4 _aUser Interfaces and Human Computer Interaction.
650 2 4 _aStatistics for Social Science, Behavorial Science, Education, Public Policy, and Law.
700 1 _aRobertson, Judy.
_eeditor.
700 1 _aKaptein, Maurits.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319266312
830 0 _aHuman-Computer Interaction Series,
_x1571-5035
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-26633-6
912 _aZDB-2-SCS
942 _cEBK
999 _c54460
_d54460