Why are some studies done with small sample sizes that ultimately make the results unreliable?
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Small studies can confirm or refute the viability of larger studies. It’s a test of the procedures and can help determine if it’s even possible to demonstrate what they’re trying to demonstrate.
Studies are expensive, and the bigger they are the more expensive they are and the longer they take. Really good data 2 years later isn’t as useful as pretty good data in two weeks.
So, you do the quick study and based on that you decide to look in a different direction or spend more on a bigger study. When some pop-sci reporter reads your small study and splashes it on a headline, it’s really not the scientist’s fault.
Sometimes studies are done because there is an obvious social/economic or environmental gain in getting data that we can then use to make informed decisions. These will most likely be publicly funded.
You can then get research or data study that is trying to achieve an outcome. Best example I can give is of lion bar (the chocolate bar) doing research for their ice cream, that concluded women prefer men with a ‘dad bod’ and a ‘belly’. Which is convenient considering their trying to sell tubs of chocolatey ice cream. If they wanted to test this robustly, they would have to use a bigger sample size and several sample sets, to ensure they didnt just pick an accidentally biased group of people. This sort of study, is ultimately almost pointless, but it can be used for marketing campaigns and as the basis of an interesting topic of conversation. But it will always be done and paid for by people (companies) who stand to benefit if the results go a certain way.
To test if a similar study could even function at a larger scale. It’s meant to be repeated over and over again
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