Anybody who studied a bit of probability theory knows that this is both false and wrong.
Statistically significant sampling can't be done with only five users.
Confidence will only be reasonably sufficient for a population of 5 (at most). This is like if you addressed your product to 5 people (I don't believe it to be likely, you probably have way more than 5 users).
Yes and no, people have relatively convergent views on usability. Statistically, you can think of proposition A "user from set U affirms that object O has property Q". You then sample opinions for U on whether this proposition is true. Each sampling is a Bernoulli trial parametrized by
p = Prob(A = True)
The standard error of the mean is then
sqrt(p*(1-p)/N)
where N is how many users you sampled. Suppose people are convergent in their opinion (either p=0.99 or 0.01) then even with N=5 the uncertainty in mean is less than 5%!
To make a concrete example, you only need to ask very few users if a particular object is white to be fairly confident whether the majority of people would consider a particular object to be white.
That is to say, if all five of the users with whom you've tested your application say it's confusing, or it sucks somehow, it is diminishingly likely for that population to be the outlier [0], and if only you had tested with a few tens or dozens — let alone thousands — more, you'd see the true pattern...
Yes, statistically, it's possible for outliers to bunch like that. It's also, statistically, far less likely.
[0] Assuming, for sake of argument, a nominally representative test group.
Anybody who studied a bit of probability theory knows that all this depends on the underlying probability distributions. If one draws five samples from a Gaussian distributions with an unknown mean and a standard deviation of 10, and none of the samples is below 50, then indeed it is very unlikely that the mean is 20.
What you're missing is covered in the article: the purpose of testing is to improve the product, not accurately document all the problems with one iteration of it. Better to test with 3 sessions of 5 users, than 1 session of 15.
See this page for assistance with computing sample size function of population and confidence https://www.surveymonkey.com/mp/sample-size-calculator/
This article probably keeps being reposted because some people try to save money on user testing
...and that's probably why we keep having sh*tty products out in the wild.