Improving the User Experience through Practical Data Analytics: Gain Meaningful Insight and Increase Your Bottom Line

✍ Scribed by Mike Fritz, Paul D. Berger

• Publisher: Morgan Kaufmann
• Year: 2015
• Tongue: English
• Leaves: 379
• Edition: 1
• Category: Library

✦ Synopsis

Improving the User Experience through Practical Data Analytics shows you how to make UX design decisions based on data—not hunches. Authors Fritz and Berger help the UX professional recognize the enormous potential of user data that is collected as a natural by-product of routine UX research methods, including moderated usability tests, unmoderated usability tests, surveys, and contextual inquiries. Then, step-by-step, they explain how to utilize both descriptive and predictive statistical techniques to gain meaningful insight with that data. By mastering the use of these techniques, you’ll delight your users, increase your bottom line and gain a powerful competitive advantage for your company—and yourself.

Key features include:

• Practical advise on choosing the right data analysis technique for each project.
• A step-by-step methodology for applying each technique, including examples and scenarios drawn from the UX field.
• Detailed screen shots and instructions for performing the techniques using Excel (both for PC and Mac) and SPSS.
• Clear and concise guidance on interpreting the data output.
• Exercises to practice the techniques, along with access to sample data on the companion website.

• Practical guidance on choosing the right data analysis technique for each project.
• Real-world examples to build a theoretical and practical understanding of key concepts from consumer and financial verticals.
• A step-by-step methodology for applying each predictive technique, including detailed examples.
• A detailed guide to interpreting the data output and examples of how to effectively present the findings in a report.
• Exercises to learn the techniques, along with access to sample data on the companion website.

✦ Table of Contents

Content:
Advance Praise for Improving the User Experience through Practical Data Analytics, Pages i-ii
Front Matter, Page v
Copyright, Page vi
Dedication, Page vii
Preface, Pages xv-xviii
About the Authors, Pages xix-xx
Acknowledgments, Pages xxi-xxii
Chapter 1 - Introduction to a variety of useful statistical ideas and techniques, Pages 1-45
Chapter 2 - Comparing two designs (or anything else!) using independent sample T-tests, Pages 47-69
Chapter 3 - Comparing two designs (or anything else!) using paired sample T-tests, Pages 71-89
Chapter 4 - Pass or fail? Binomial-related hypothesis testing and confidence intervals using independent samples, Pages 91-117
Chapter 5 - Pass or fail? Binomial-related hypothesis testing and confidence intervals using paired samples, Pages 119-134
Chapter 6 - Comparing more than two means: One factor ANOVA with independent samples. Multiple comparison testing with the Newman-Keuls test, Pages 135-161
Chapter 7 - Comparing more than two means: One factor ANOVA with a within-subject design, Pages 163-185
Chapter 8 - Comparing more than two means: Two factor ANOVA with independent samples: the important role of interaction, Pages 187-204
Chapter 9 - Can you relate? Correlation and simple linear regression, Pages 205-237
Chapter 10 - Can you relate in multiple ways? Multiple linear regression and stepwise regression, Pages 239-269
Chapter 11 - Will anybody buy? Logistic regression, Pages 271-304
Addendum: For Mac Excel Users, Pages 305-368
Index, Pages 369-374