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Improving the user experience through practical data analytics : gain meaningful insight and increase your bottom line  Cover Image E-book E-book

Improving the user experience through practical data analytics : gain meaningful insight and increase your bottom line

Fritz, Mike (author.). Berger, Paul D., 1943- (author.).

Summary: Improving the User Experience through Practical Data Analytics is your must-have resource for making UX design decisions based on data, rather than hunches. Authors 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. You'll be.

Record details

  • ISBN: 9780128006351
  • ISBN: 9780128006351
  • ISBN: 0128006358
  • ISBN: 0128006781
  • ISBN: 9780128006788
  • Physical Description: 1 online resource (1 volume) : illustrations
    remote
  • Publisher: Waltham, MA : Morgan Kaufmann, [2015]

Content descriptions

Bibliography, etc. Note: Includes bibliographical references and index.
Formatted Contents Note: Chapter 5 -- Pass or fail? Binomial-related hypothesis testing and confidence intervals using paired samples5.1 INTRODUCTION; 5.3 HYPOTHESIS TESTING USING THE COCHRAN Q TEST; 5.4 MEANWHILE, BACK AT BACKBOARD ... ; 5.5 SUMMARY; 5.6 EXERCISE; REFERENCES; Chapter 6 -- Comparing more than two means: one factor ANOVA with independent samples. Multiple comparison testing with the Newman-Keuls test; 6.1 INTRODUCTION; 6.2 CASE STUDY: SOPHISTICATED FOR WHOM?; 6.3 INDEPENDENT SAMPLES: ONE-FACTOR ANOVA; 6.4 THE ANALYSES; 6.5 MULTIPLE COMPARISON TESTING; 6.6 ILLUSTRATION OF THE S-N-K TEST.
Source of Description Note:
Print version record.
Subject: Data mining
Quantitative research
Exploration de données (Informatique)
Recherche quantitative
Data mining
Quantitative research
Genre: Electronic books.

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