L'analyse de données UX
Master UX data analysis techniques from qualitative research to Big Data analytics and extract valuable insights to create friction-free user experiences.
Master UX data analysis techniques from qualitative research to Big Data analytics and extract valuable insights to create friction-free user experiences.
Become a UX data scientist with this comprehensive course that bridges Big Data and UX. Learn essential methods and tools for analyzing the full spectrum of UX data, from qualitative analysis to web analytics. Taught by award-winning professors, this course equips you to extract valuable insights from data and formulate evidence-based recommendations to create optimal, friction-free user experiences. The curriculum covers descriptive statistics, study design, bias sources, hypothesis testing, mean comparisons, two-factor ANOVA, and practical applications in user experience. No prior statistics knowledge is required, though access to Excel software is necessary for certification completion. Discover what lies behind UX data analysis through this accessible course, designed for professionals seeking to enhance their analytical skills in user experience design.
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What you'll learn
Learn descriptive statistics techniques essential for organizing and summarizing UX data Master study design principles to ensure valid and reliable user research Identify and mitigate various sources of bias that can affect UX research outcomes Conduct hypothesis testing to validate assumptions about user behavior Perform mean comparisons to identify significant differences in user interactions Apply two-factor ANOVA for complex analysis of user experience variables Translate statistical findings into actionable UX improvements
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
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Module Description
This comprehensive course covers the essential methods and tools for analyzing UX data across the spectrum, from qualitative analysis to web analytics. The curriculum begins with foundational concepts in descriptive statistics before diving into study design principles and understanding various sources of bias that can affect research outcomes. Students will learn practical hypothesis testing techniques and how to effectively compare means to draw meaningful conclusions from user data. The course also covers two-factor ANOVA, providing more advanced statistical analysis capabilities. Throughout the program, all concepts are directly applied to user experience contexts, showing how data analysis can inform better UX decisions. The course is designed to be accessible to professionals without prior statistical knowledge, focusing on practical applications rather than theoretical concepts. By the end of the course, participants will be able to extract valuable insights from UX data and formulate evidence-based recommendations to create optimal, friction-free user experiences.
Fee Structure
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Instructors
8 Courses
Probability and Financial Engineering Expert at HEC Montréa
Chantal Labbé, Associate Professor at HEC Montréal, specializes in stochastic processes, financial engineering, and portfolio optimization, with award-winning teaching in decision sciences.
8 Courses
Leading Statistician and User Experience Researcher at HEC Montréal
Marc Fredette, Professor at HEC Montréal, specializes in biostatistics, Bayesian stats, and longitudinal data analysis, advancing UX research and education.
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Frequently asked questions
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