Synopsis
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.
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