Improving the user experience through practical data analytics : gain meaningful insight and increase your bottom line /
By: Fritz, Mike.
Contributor(s): Berger, Paul D.
Publisher: Boston : Morgan Kaufmann is an imprint of Elsevier, 2015Description: xxii, 374 pages : illustrations ; 23 cm.Content type: text | text | still image Media type: unmediated | unmediated Carrier type: volume | volumeISBN: 0128006358; 9780128006351:; 9780128006351.Subject(s): Data mining | Quantitative researchDDC classification: 006.312Item type | Current library | Call number | Status | Date due | Barcode | Item holds |
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Standard Loan | ATU Sligo Yeats Library Main Lending Collection | 006.312 FRI (Browse shelf(Opens below)) | Available | 0062738 |
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.