Includes bibliographical references and index.

Preface -- About the authors -- Acknowledgements -- Introduction to a variety of useful statistical ideas and techniques -- Comparing two designs (or anything else!) using independent sample T-tests -- Comparing two designs (or anything else!) using paired sample T-tests -- Pass or fail? Binomial-related hypothesis testing and confidence intervals using independent samples -- Pass or fail? Binomial-related hypothesis testing and confidence intervals using paired samples -- Comparing more than two means : one factor ANOVA with independent samples. Multiple comparison testing with the Newman-Keuls test -- Comparing more than two means : one factor ANOVA with a within-subject design -- Comparing more than two means : two factor ANOVA with independent samples; the important role of interaction -- Can you relate? Correlation and simple linear regression -- Can you relate in multiple ways? Multiple linear regression and stepwise regression -- Will anybody buy? Logistic regression.

'Improving the User Experience through Practical Data Analytics' is a must-have resource for making UX design decisions based on data, rather than hunches. Fritz and Berger help the UX professional recognize and understand the enormous potential of the ever-increasing user data that is often accumulated as a by-product of routine UX tasks, such as conducting usability tests, launching surveys, or reviewing clickstream information. Then, step-by-step, they explain how to utilize both descriptive and predictive statistical techniques to gain meaningful insight with that data.