Practical Statistics for The User Experience I
Description
Measurement is important but statistics can be intimidating. In this Practical Statistics for User Experience (UX) Course we will present approachable concepts and lots examples for generating statistical solutions to common questions in user research. The presentation includes many graphical representations and a "What test do I use?" decision tree.
Is Design A more usable than Design B? Do more users convert on the new design? Is our Net Promoter Score statistically better than last year?
Learn to use and interpret the right statistical tests on small and large sample user-data using just Excel. We will cover:
- Sampling Fundamentals
- The Normal Distribution
- Confidence Intervals
- Comparing Means and Proportions
- Understanding what statistical test to perform and how to perform it
- Interpreting p-values
- Reporting and Explaining Statistical Significance to Stakeholders
- Making better decsions with data and understanding uncertainty and risk
This course is course number E 60.2 from a comprehensive curriculum on User experience (UX) currently under development at The Online User eXperience Institute (OUXI).
Course content
- Preview11:12
- 336 pagesExcel & R Companion to Quantifying the User Experience
- 1.7 MBStats Usability Pak Lite
- 05:23Fundamentals Continued (Includes The Normal Distribution)
Instructor
![Jeff Sauro](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 3.7 Instructor Rating
- 247 Reviews
- 4,913 Students
- 1 Course
Jeff is a Six-Sigma trained statistical analyst and pioneer in quantifying the user experience. He specializes in making statistical concepts understandable and actionable. Jeff has published over fifteen peer-reviewed research articles and presents tutorials and papers regularly at the leading Human Computer Interaction conferences: CHI, UPA and HCII and HFES. He is author of four books including: Quantifying the User Experience: Practical Statistics for User Research (Morgan Kaufmann).
He has worked for GE, Intuit, PeopleSoft and Oracle and has consulted with dozens of Fortune 500 companies.
Jeff received his Masters in Learning, Design and Technology from Stanford University with a concentration in statistical concepts. Prior to Stanford, he received his B.S. in Information Management & Technology and BS in Television, Radio and Film from Syracuse University. While at Syracuse he completed a two-year thesis study on web-usability.
Jeff is a Six-Sigma trained statistical analyst and pioneer in quantifying the user experience. He specializes in making statistical concepts understandable and actionable. Jeff has published over fifteen peer-reviewed research articles and presents tutorials and papers regularly at the leading Human Computer Interaction conferences: CHI, UPA and HCII and HFES. He is author of the forthcoming book: Quantifying the User Experience: Practical Statistics for User Research (Morgan Kaufman, March 2012). He has worked for GE, Intuit, PeopleSoft and Oracle and has consulted with dozens of Fortune 500 companies.