Wondering about the origins of the sample size controversy in the usability profession? Here is an annotated timeline of the major events and papers which continue to shape this topic. The Pre-Cambrian Era (Up to 1982) It’s the dawn of Usability Evaluation and the first indications of diminishing returns in problem discovery are emerging. 1981:
Will users purchase an upgrade? What features are most desired? Will they recommend the product to a friend? Part of measuring the user experience involves directly asking users what they think via surveys. The Web has made surveys easy to administer and deliver. It hasn’t made the question of how many people you need to
With usability testing it used to be that we had to make our best guess as how users actually interacted with software outside a contrived lab-setting. We didn’t have all the information we needed. Knowing what users did was in a sense a puzzle with a lot of missing pieces. Web-analytics provides us with a
Usability tests are conducted on samples of users taken from a larger user population. In usability testing it is hard enough to recruit and test users let alone select them randomly from the larger user population. Samples in usability studies are almost always convenience samples. That is, we rely on volunteers to participate in our
If you ask five users to take a look at a website or application you will find usability problems. If you fix those problems then ask another five users you will get another set of problems. Over time there will be fewer and fewer problems found, but a new set of users will still continue
One question I get a lot is, Do you really only need to test with 5 users? There are a lot of strong opinions about the magic number 5 in usability testing and much has been written about it (e.g. see Lewis 2006PDF). As you can imagine there isn’t a fixed number of users that
Nielsen derives his “five users is enough” formula from a paper he and Tom Landauer published in 1993. Before Nielsen and Landauer James Lewis of IBM proposed a very similar problem detection formula in 1982 based on the binomial probability formula.[4] Lewis stated that: The binomial probability theorem can be used to determine the probability
One of the biggest and usually first concerns levied against any statistical measures of usability is that the number of users required to obtain “statistically significant” data is prohibitive. People reason that one cannot with any reasonable level of confidence employ quantitative methods to determining product usability. The reasoning continues something like this: “I have
We already saw how a manageable sample of users can provide meaningful data for discrete-binary data like task completion. With continuous data like task times, the sample size can be even smaller. The continuous calculation is a bit more complicated and involves somewhat of a Catch-22. Most want to determine the sample size ahead of
