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|a 905992661
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|a 9780128006788
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|a 9780128006351
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|a UAMI
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|a Fritz, Mike,
|e author.
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|a Improving the user experience through practical data analytics :
|b gain meaningful insight and increase your bottom line /
|c Mike Fritz, Paul D. Berger.
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|a Waltham, MA :
|b Morgan Kaufmann,
|c [2015]
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|c ©2015
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|a 1 online resource (1 volume) :
|b illustrations
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|a text
|b txt
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a Print version record.
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|a Includes bibliographical references and index.
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|a Front Cover; Advance Praise for Improving the User Experience through Practical Data Analytics; Improving the User Experience through Practical Data Analytics; Copyright; Dedication; Contents; Preface; WHY WE WROTE THE BOOK; HOW THIS BOOK IS SPECIAL; THE SOFTWARE WE USE; WHAT YOU NEED TO ALREADY KNOW; ORGANIZATION AND COVERAGE; EXERCISES AND SUPPLEMENTARY MATERIAL; About the Authors; MIKE FRITZ; PAUL D. BERGER; ABOUT THE ILLUSTRATOR: RICK PINCHERA; Acknowledgments; Chapter 1 -- Introduction to a variety of useful statistical ideas and techniques; 1.1 INTRODUCTION.
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|a 1.2 THE GREAT NORMAL CURVE IN THE SKY1.3 CONFIDENCE INTERVALS; 1.4 HYPOTHESIS TESTING; 1.5 SUMMARY; 1.6 ADDENDUM: ACTIVATING "DATA ANALYSIS"; REFERENCES; Chapter 2 -- Comparing two designs (or anything else!) using independent sample T-tests; 2.1 INTRODUCTION; 2.2 CASE STUDY: COMPARING DESIGNS AT MADEMOISELLE LA LA; 2.3 COMPARING TWO MEANS; 2.4 INDEPENDENT SAMPLES; 2.5 MADEMOISELLE LA LA REDUX; 2.6 BUT WHAT IF WE CONCLUDE THAT THE MEANS AREN'T DIFFERENT?; 2.7 FINAL OUTCOME AT MADEMOISELLE LA LA; 2.8 ADDENDUM: CONFIDENCE INTERVALS; 2.9 SUMMARY; 2.10 EXERCISE; REFERENCE.
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|a Chapter 3 -- Comparing two designs (or anything else!) using paired sample T-tests3.1 INTRODUCTION; 3.2 VIGNETTE: HOW FAST CAN YOU POST A JOB AT BEHEMOTH.COM?; 3.3 INTRODUCTION TO PAIRED SAMPLES; 3.4 EXAMPLE OF PAIRED (TWO-SAMPLE) T-TEST; 3.5 BEHEMOTH.COM REVISITED; 3.6 ADDENDUM: A MINI-DISCUSSION WHY THE INDEPENDENT AND PAIRED TESTS NEED TO BE DIFFERENT; 3.7 SUMMARY; 3.8 EXERCISE; REFERENCES; Chapter 4 -- Pass or fail? Binomial-related hypothesis testing and confidence intervals using independent samples; 4.1 INTRODUCTION.
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|a 4.2 case study: is our expensive new search engine at behemoth.com better than what we already have?4.3 hypothesis testing using the chi-square test of independence or fisher's exact test; 4.4 meanwhile, back at behemoth.com; 4.5 binomial confidence intervals and the adjusted wald method; 4.6 summary; 4.7 addendum 1: how to run the chi-square test for different sample sizes; 4.8 addendum 2: comparing more than two treatments; 4.9 appendix: confidence intervals for all possible sample-proportion outcomes from n = 1 to n = 15, in table a.1; 4.10 exercises; references.
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|a 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.
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|a 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.
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590 |
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|a O'Reilly
|b O'Reilly Online Learning: Academic/Public Library Edition
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650 |
|
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|a Data mining.
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650 |
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|a Quantitative research.
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650 |
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6 |
|a Exploration de données (Informatique)
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650 |
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|a Recherche quantitative.
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650 |
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7 |
|a Data mining.
|2 fast
|0 (OCoLC)fst00887946
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650 |
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7 |
|a Quantitative research.
|2 fast
|0 (OCoLC)fst01742283
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700 |
1 |
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|a Berger, Paul D.,
|d 1943-
|e author.
|
776 |
0 |
8 |
|i Print version:
|a Fritz, Mike.
|t Improving the user experience through practical data analytics
|z 9780128006788
|w (OCoLC)894611890
|
856 |
4 |
0 |
|u https://learning.oreilly.com/library/view/~/9780128006351/?ar
|z Texto completo (Requiere registro previo con correo institucional)
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938 |
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|a EBL - Ebook Library
|b EBLB
|n EBL1990683
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994 |
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