This is a pretty solid recommendation. For those who are more interested in the details, there is some nuance here.
In most cases, we as UX'ers are talking about Formative (what mistakes will users make) versus Summative (statistically, how many people will succeed).
As you point out, the general consensus is a population size of 5 will deliver the best cost to benefit ratio. There are two scenarios where that doesn't necessarily hold true.
The first, is if you only get one round of usability testing. While unfortunate, it happens–In that case, go for more as it's your only shot.
The second, is when the probability of finding a mistake is very low. The following chart shows the chances of detecting a problem given the sample size and probability of seeing event once (think of dice, d3 versus d20).
You can read the original magic number five article here if you want. Also, since everyone cites Nielsen I think it's prudent to point out that some of the credit should go to Bob Virzi and James Lewis who did a bunch of earlier work on this topic.
I'd be happy to go into the nuance of the topic of Summative sample sizes but that gets deep into statistics which is no fun to write up...
This is a pretty solid recommendation. For those who are more interested in the details, there is some nuance here.
In most cases, we as UX'ers are talking about Formative (what mistakes will users make) versus Summative (statistically, how many people will succeed).
As you point out, the general consensus is a population size of 5 will deliver the best cost to benefit ratio. There are two scenarios where that doesn't necessarily hold true.
The first, is if you only get one round of usability testing. While unfortunate, it happens–In that case, go for more as it's your only shot.
The second, is when the probability of finding a mistake is very low. The following chart shows the chances of detecting a problem given the sample size and probability of seeing event once (think of dice, d3 versus d20).
You can read the original magic number five article here if you want. Also, since everyone cites Nielsen I think it's prudent to point out that some of the credit should go to Bob Virzi and James Lewis who did a bunch of earlier work on this topic.
I'd be happy to go into the nuance of the topic of Summative sample sizes but that gets deep into statistics which is no fun to write up...