Arrghh. The quintessential anova experiments by cobb were done on 8 data points.
All groups are different. Let me repeat. All groups have different means. The magnitude of the difference (difference between means) is called the effect size. If the effect is large you need a trivial amounts of data. If the effect is small you need lots.
The only thing p is telling you is whether you can reliably tell the datasets apart. It's NOT telling you how far the datasets are apart, which is what you really want to know - does this change cause a large difference.
All groups are different. Let me repeat. All groups have different means. The magnitude of the difference (difference between means) is called the effect size. If the effect is large you need a trivial amounts of data. If the effect is small you need lots.
The only thing p is telling you is whether you can reliably tell the datasets apart. It's NOT telling you how far the datasets are apart, which is what you really want to know - does this change cause a large difference.