Why do scientific experiments (mainly in neuroscience and psychology) need to be done on more than 1 person? I was under the impression that the most important part of determining the study’s accuracy was to ensure that the outcome had a less than 5% chance of occurring without the theorised variable.
Couldn’t a situation emerge where the outcome was almost certainly attributed to the variable in question even with one person. For example, something extremely random, like (stupid example) a blood clot forming in someone’s left pinky finger after being reminded of childhood trauma (and it was predicted beforehand).
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Experiments require controls. You can do observational research on a single subject, but you could never ever do an experiment.
Let’s consider a silly, but precisely defined, experiment. I have a red pigment. I hypothesize that if I apply this red pigment to a person’s hand, their hand will be red. I take a single subject, apply the pigment to their hand, and measure how red their hand is (using some objective measure of, like, wavelength absorption).
From this, I can conclude that the subject’s hand was a certain amount of red after application of the pigment, but I can’t conclude anything else. I need something to *compare* my measurement to in order to determine that the pigment made their hand *more* red. The most straightforward way (in terms of the scientific method) is to compare the treated subject to a control subject who did not get the pigment.
Another way to obtain a point of comparison is to measure the subject’s hand bothe before and after application of the pigment. In this case I still have one person participating, but their past self is serving as the control, and their future self is treated. This is not ideal because there other things that may be changing over time that could affect what I’m trying to measure.
Either way, you need a point of comparison to perform the experiment, and once you’re comparing two things, you need to be able to characterize the probability that they are different by chance rather than due to the treatment. That’s where statistics and p-values come in.
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