Course Description

Get ready to dive into the exciting world of Big Data and User Experience (UX) with this comprehensive MOOC that bridges the gap between qualitative analysis and web analytics. Designed by award-winning professors, this course offers an accessible introduction to statistical methods and tools essential for analyzing UX data. Whether you're a beginner or looking to expand your skill set, this course will equip you with the knowledge to extract valuable insights from data and create friction-free, optimal user experiences.

What Students Will Learn

• Descriptive statistics
• Study design principles
• Identification and mitigation of bias sources
• Hypothesis testing techniques
• Mean comparison methods
• Two-factor ANOVA (Analysis of Variance)
• Practical applications of statistical methods in user experience

Prerequisites

No prior knowledge of statistics is required. However, access to Microsoft Excel is necessary for completing the certification exam. For those pursuing the MicroMasters in UX Design and Evaluation, it is strongly recommended to complete the "Introduction to UX" (UXf01x.1) and "UX Research" (UXf01x.1) courses before enrolling in this one.

Course Coverage

• The spectrum of data analyzed in UX, from qualitative analysis to web analytics
• Methods and tools for extracting meaningful information from UX data
• Formulation of empirically-based recommendations for optimal user experiences
• Statistical techniques and their application in UX design and evaluation
• Practical use of Excel for data analysis and interpretation

Who This Course Is For

• UX designers and researchers looking to enhance their data analysis skills
• Professionals interested in the intersection of Big Data and user experience
• Students pursuing a career in UX design, data science, or web analytics
• Anyone curious about how data can inform better user experiences

Real-World Applications

• Improving website and app design based on data-driven insights
• Conducting more effective user research and usability testing
• Making informed decisions about UX improvements in professional settings
• Enhancing digital marketing strategies through better understanding of user behavior
• Contributing to data-driven design processes in various industries

Syllabus Overview

1. Introduction to UX data analysis
2. Descriptive statistics in UX context
3. Study design and methodology
4. Identifying and addressing bias in UX research
5. Hypothesis testing for UX decisions
6. Comparing means in user studies
7. Two-factor ANOVA for complex user comparisons
8. Applying statistical methods to real-world UX challenges
9. Using Excel for UX data analysis and visualization

This course is part of the MicroMasters® Program in Design et Évaluation UX offered by HECMontrealX, providing a solid foundation for those looking to advance their careers in UX design and evaluation.