What should you do when your sample doesn’t match the known population composition on key variables like prior experience? One approach is to weight your data to rebalance the sample. In a previous article, we discussed how to weight means (such as from rating scales) when there are differences between group proportions in a sample
You’re 25% complete. Still a ways to go. You got a score of 90 out of 100 on a math test. Not bad. You got 1475 on the SAT—the 95th percentile. Awesome! Only 40% of users completed the task. Not great. The average score on a seven-point scale was 5.2. Hmm. Is that good? One
It’s common in UX research to encounter percentages: 90% task completion rates 10% reduction in time 250% increase in mean scores −20% Net Promoter Score −10% new UX jobs Despite their familiarity, their interpretation can be tricky because the same term (“percentage”) is associated with distinctly different concepts. The three key types are: Absolute percentages
