Paul D. Berger – författare

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 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

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- 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

This text introduces and provides instruction on the design and analysis of experiments for a broad audience. Formed by decades of teaching, consulting, and industrial experience in the Design of Experiments field, this new edition contains updated examples, exercises, and situations covering the science and engineering practice. This text minimizes the amount of mathematical detail, while still doing full justice to the mathematical rigor of the presentation and the precision of statements, making the text accessible for those who have little experience with design of experiments and who need some practical advice on using such designs to solve day-to-day problems. Additionally, an intuitive understanding of the principles is always emphasized, with helpful hints throughout.