When evaluating data or developing conclusions, UX researchers may make statistical errors. Being aware of these common errors and adhering to best practices in study design, data collecting, and analysis can help researchers reduce errors and improve the quality of their research findings. These are explanations and examples of the most typical statistical errors:
Picture this: you’re analyzing customer feedback and everything seems to point to a single average sentiment. You conclude that most...
In my statistics courses, I always emphasize that whether you want to be a UX researcher, a Human Factors specialist, a cognitive...
In my courses requiring individual projects, students often ask how many participants they need. They expect a simple answer like “20” or...
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