book

Improving the User Experience through Practical Data Analytics

by Mike Fritz, Paul D. Berger

March 2015

Beginner to intermediate

396 pages

10h 23m

English

Morgan Kaufmann

Read now

Unlock full access

Cover image
Title page
Table of Contents
Advance Praise for Improving the User Experience through Practical Data Analytics
Copyright
Dedication
Preface
About the Authors
Acknowledgments
Chapter 1. Introduction to a variety of useful statistical ideas and techniques
1.1. Introduction1.2. The Great Normal Curve in the Sky1.3. Confidence Intervals1.4. Hypothesis Testing1.5. Summary1.6. Addendum: activating “Data Analysis”

Chapter 2. Comparing two designs (or anything else!) using independent sample T-tests
2.1. Introduction2.2. Case Study: Comparing Designs at Mademoiselle La La2.3. Comparing Two Means2.4. Independent Samples2.5. Mademoiselle La La Redux2.6. But What if We Conclude that the Means Aren’t Different?2.7. Final Outcome at Mademoiselle La La2.8. Addendum: Confidence Intervals2.9. Summary2.10. Exercise
Chapter 3. Comparing two designs (or anything else!) using paired sample T-tests
3.1. Introduction3.2. Vignette: How Fast Can You Post a Job at Behemoth.com?3.3. Introduction to Paired Samples3.4. Example of Paired (Two-Sample) t-test3.5. Behemoth.com Revisited3.6. Addendum: A Mini-Discussion Why the Independent and Paired Tests Need to Be Different3.7. Summary3.8. Exercise
Chapter 4. Pass or fail? Binomial-related hypothesis testing and confidence intervals using independent samples
4.1. Introduction4.2. 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 Test4.4. Meanwhile, Back At Behemoth.Com4.5. Binomial Confidence Intervals and the Adjusted Wald Method4.6. Summary4.7. Addendum 1: How to Run the Chi-Square Test for Different Sample Sizes4.8. Addendum 2: Comparing More than Two Treatments4.9. Appendix: Confidence Intervals for all Possible Sample-Proportion Outcomes From N = 1 to N = 15, in Table A.14.10. Exercises
Chapter 5. Pass or fail? Binomial-related hypothesis testing and confidence intervals using paired samples
5.1. Introduction5.2. Case Study: Can I Register for a Course at Backboard.com?5.3. Hypothesis testing using the cochran Q test5.4. Meanwhile, back at backboard…5.5. Summary5.6. Exercise
Chapter 6. Comparing more than two means: one factor ANOVA with independent samples. Multiple comparison testing with the Newman-Keuls test
6.1. Introduction6.2. Case Study: Sophisticated for Whom?6.3. Independent Samples: One-Factor ANOVA6.4. The Analyses6.5. Multiple Comparison Testing6.6. Illustration of the S-N-K Test6.7. Application of the S-N-K to This Result6.8. Discussion of the Result6.9. Meanwhile, Back at Mademoiselle La La…6.10. Summary6.11. Exercises
Chapter 7. Comparing more than two means: one factor ANOVA with a within-subject design
7.1. Introduction7.2. Case Study: Comparing Multiple Ease-of-Use Ratings at Mademoiselle La La7.3. Comparing Several Means with a Within-Subjects Design7.4. Hypotheses for Comparing Several Means7.5. SPSS Analysis7.6. Newman-Keuls Analysis7.7. Excel Analysis7.8. Mademoiselle La La: Let’s Fix the Checkout Asap!7.9. Summary7.10. Exercise
Chapter 8. Comparing more than two means: two factor ANOVA with independent samples; the important role of interaction
8.1. Introduction8.2. Case Study: Comparing Age and Gender at Mademoiselle La La8.3. Interaction8.4. Working the example in SPSS8.5. Meanwhile, back at Mademoiselle La La…8.6. Summary8.7. Exercise
Chapter 9. Can you relate? Correlation and simple linear regression
9.1. Introduction9.2. Case Study: Do Recruiters Really Care about Boolean at Behemoth.Com?9.3. The Correlation Coefficient9.4. Linear Regression9.5. Linear Regression Analysis of Behemoth.com Data9.6. Meanwhile, Back at Behemoth9.7. Summary9.8. Addendum: A Quick Discussion of Some Assumptions Implicit in Interpreting the Results9.9. Exercise
Chapter 10. Can you relate in multiple ways? Multiple linear regression and stepwise regression
10.1. Introduction10.2. Case Study: Determining the Ideal Search Engine at Behemoth.Com10.3. Multiple Regression10.4. A Confidence Interval for the Prediction10.5. Back to Behemoth.Com10.6. Stepwise Regression10.7. Meanwhile, Back at Behemoth.com10.8. Summary10.9. Exercise
Chapter 11. Will anybody buy? Logistic regression
11.1. Introduction11.2. Case study: will anybody buy at the Charleston Globe?11.3. Logistic regression11.4. Logistic regression using SPSS11.5. CharlestonGlobe.com survey data and its analysis11.6. Implications of the survey-data analysis results—Back to CharlestonGlobe.com11.7. Summary11.8. Exercise
Addendum: For Mac Excel Users
Index

Content preview from Improving the User Experience through Practical Data Analytics

Cover image

Title page

Advance Praise for Improving the User Experience through Practical Data Analytics

Chapter 1. Introduction to a variety of useful statistical ideas and techniques

1.1. Introduction

1.2. The Great Normal Curve in the Sky

1.3. Confidence Intervals

1.4. Hypothesis Testing

1.5. Summary

1.6. Addendum: activating “Data Analysis”

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. ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.

Read now

Unlock full access

More than 5,000 organizations count on O’Reilly

O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.

Julian F.

Head of Cybersecurity

I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.

Addison B.

Field Engineer

I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.

Amir M.

Data Platform Tech Lead

I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.

Mark W.

Embedded Software Engineer

Publisher Resources

ISBN: 9780128006351

Cloud Computing

Data Engineering

Data Science

AI & ML

Programming Languages

Software Architecture

IT/Ops

Security

Design

Business

Soft Skills

Improving the User Experience through Practical Data Analytics

by Mike Fritz, Paul D. Berger

Table of Contents

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.