Researchers involved in a recent study trained an artificial intelligence (AI) model to diagnose type 2 diabetes in patients after six to 10 seconds of listening to their voice. Canadian medical researchers trained the machine-learning AI to recognise 14 vocal differences in the voice of someone with type 2 diabetes compared to someone without diabetes. […]
Sample size is relevant as a proportion of the difference you are looking for.
For example:
Sample A:
1.1,
1.3,
1.5,
1.2,
1.1
Sample B:
345.3,
323.4,
322.3,
355.2
Determining a statistical difference between these two groups where a meaningful difference is 20%, does not require more samples. The chance of error on making a claim that A is less than B will be quite low.
Not saying that N=18 in this case is sufficient, just stating that the number alone does not give you enough information to determine whether a claim has weight to it or not.
Sample size is relevant as a proportion of the difference you are looking for.
For example:
Sample A: 1.1, 1.3, 1.5, 1.2, 1.1
Sample B: 345.3, 323.4, 322.3, 355.2
Determining a statistical difference between these two groups where a meaningful difference is 20%, does not require more samples. The chance of error on making a claim that A is less than B will be quite low.
Not saying that N=18 in this case is sufficient, just stating that the number alone does not give you enough information to determine whether a claim has weight to it or not.