[EllaMentry]

"The participant pool was composed entirely of 72 female students at the University of Texas at Austin, because researchers were unable to find male participants who played computer games for less than two hours a day."

The sample size seems far too small and narrow to draw any conclusions from.

[chid]

Sample size has nothing (not strictly true) to do with whether a result is statistically significant. I imagine they chose this sample size because it could potentially yield a statistically significant sample.

A larger sample size means that a smaller average increase is required to show that it is a statistically significant deviation than a smaller sample.

[lutusp]

> Sample size has nothing (not strictly true) to do with whether a result is statistically significant.

I hate to rain on your parade, but sample size has everything to do with whether a result is statistically significant.

http://sph.bu.edu/otlt/MPH-Modules/BS/BS704_Power/BS704_Powe...

[wisty]

No, almost any sample size can be sufficient, as long as the effect is big enough. Though in psychology, larger samples are often needed, because there's generally smaller effects.

If you want to test whether penicillin can cure a staph infection, you can get statistically significant results with a handful of tests.

[lutusp]

>> Sample size has nothing (not strictly true) to do with whether a result is statistically significant.

>> I hate to rain on your parade, but sample size has everything to do with whether a result is statistically significant.

> No, almost any sample size can be sufficient, as long as the effect is big enough.

Your sentence says "no", but it agrees -- sample size has everything to do with determining statistical significance. The ratio of sample size to population is critical to deciding whether a result is significant: http://classroom.synonym.com/select-statistically-significan...

> Though in psychology, larger samples are often needed, because there's generally smaller effects.

Yes, but many of those kinds of result are insignificant and instantly forgotten regardless of the circumstances, because psychologists generally aren't testing a falsifiable theory, only measuring an "interesting" effect, like whether leaning to the left makes the Eiffel Tower look shorter (the 2012 Ig Nobel Prize winner):

Title: "Leaning to the Left Makes the Eiffel Tower Seem Smaller -- Posture-Modulated Estimation"

Link: http://pss.sagepub.com/content/early/2011/11/23/095679761142...

Ig Nobel Prize announcement: http://www.improbable.com/ig/2012/

[wisty]

Normal distribution of a sample scales with sigma, and inverse to sqrt(n-1), so effect size is more important than sample size. That's all the guy who originally posted was talking about.

I don't think anyone on hn won't know this. Everyone is just quibbling over the wording.

Your new point is very good, and I'd expect someone has used the correlation != causation argument too.

[EllaMentry]

True, however, I also noted the sample was not just small but narrow. 72, female, university students - I would be surprised if over 6-8 weeks their cognitive capacity didn't improve in a measurable way - university can be a very demanding environment.

The study makes no mention of controlling for degree programs or a variety of other factors which would affect cognitive development, combined with the incredibly small sample size, It is my opinion that any conclusions from this research need to be taken with a pinch of salt.

[rsheridan6]

They did have a control group playing the Sims, a much easier game.