Mean, median, and mode: which measure for task completion times?
This tests whether you know task times are skewed and sample size drives the mean-versus-median choice. A strong answer cites the under-25 rule, contrasts mean outlier sensitivity with median robustness, and dismisses mode. Red flag: defaulting to the mean.
What's really being asked
Whether you recognize that raw task times are non-normal and heavily right-skewed, and whether you know that the arithmetic mean is distorted by a few slow outliers while the median stabilizes only with adequate sample size. The interviewer wants to see statistical literacy applied to UX metrics, not just textbook definitions.
The full answer
First, define the three measures in one sentence. The arithmetic mean is the sum divided by the count. The median is the middle value when times are sorted. The mode is the most frequent value, which is rarely useful for continuous task times because durations are spread across many unique values. Second, state that task completion times are almost always right-skewed due to a few users who struggle or get distracted. Third, explain the sample size rule from MeasuringU: use the geometric mean for small samples under twenty-five users because it dampens the effect of outliers, and use the median for larger samples because it becomes more stable as n grows. Fourth, mention that confidence intervals should be computed after log-transforming the data, since standard parametric methods assume normality. Fifth, clarify which task time you are averaging, because the reference distinguishes between average task completion time for successful users only, mean time to failure, and average time on task regardless of outcome.
The mistakes people make
Defaulting to the arithmetic mean without mentioning skew or outliers. Claiming the median is always better without acknowledging it is less accurate for small sample sizes. Confusing average time on task with average task completion time and including failed attempts when the metric should reflect successful paths. Ignoring log transformation and proposing a plain standard deviation or standard error. Mentioning mode as a viable central tendency for continuous task times.
What usually comes next
How would you report a confidence interval for task times. When is it appropriate to exclude failed tasks from the average. How do you compare task times between two designs. What is Keystroke Level Modeling and when would you use it. How do you handle users who were obviously distracted during an unmoderated test.
A concrete example
Suppose you run a summative usability test with twenty users and collect successful task completion times. The arithmetic mean is four minutes because two users took twelve minutes after hitting a confusing label. The geometric mean is about two and a half minutes, and the median is two minutes. Because the sample is under twenty-five, you report the geometric mean and add a confidence interval derived from log-transformed data. If you had one hundred users, you would shift to the median and still log-transform for the interval. You would not report a mode because twenty continuous measurements rarely cluster on the exact same second.
Interview question
When reporting successful task times from 100 users with strong right skew, which measure does the sample size rule recommend?
- a.The geometric mean, because it dampens outliers better than the median at any sample size
- b.The arithmetic mean, since large samples eliminate the impact of outliers
- c.The median, because it becomes more stable as the sample size growsCorrect
- d.The mode, because it highlights the most common user experience
Why? this is the answer
The card states that for larger samples you should report the median because it stabilizes as n grows, while the geometric mean is reserved for samples under 25. The arithmetic mean remains distorted by outliers regardless of sample size, and the mode is rarely useful for continuous durations.
Just read this? Test yourself on what you have been reading.
Read the original → measuringu.com
- #ux research
- #statistics
- #task times
- #central tendency
- #usability metrics
Put your scrolling time to good use
Learn one idea, try a quiz and save useful cards for revision. Tezvyn makes it easy to learn and stay current in your tech field, a few minutes at a time.
The iPhone app is on the way
We are building it. Until it lands, nothing here is held back from you: every interview card, your saved cards, streaks and the job board all work in Safari, plus hundreds of free practice quizzes of thirty questions each. Sign in and it all carries over to the app the day it arrives.
Want it as an icon? Tap Share at the bottom of Safari, then Add to Home Screen. It opens full screen and the cards you have read stay available offline.
We are hiring for this. Open roles that interview on ux research — each one lists the topics its interview covers.
See open roles