Sometimes, what appears to be a bimodal distribution is actuallytwo unimodal (one-peaked) distributions graphed on the same axis.For example, this image shows a bimodal distribution for a group of students who did not study (the left peak) and a group of students whodidstudy (on the right)...
As the number of objectives increases and one is faced with a many-objective problem, it becomes more likely that the objectives are heterogeneous meaning they differ in, for example, complexity (e.g. linear vs non-linear, unimodal vs multimodal), evaluation efforts in terms of time, costs,...
If you only sample n = 30 from that population, you do get a unimodal distribution, but it’s still not quite symmetric. For this population, you need to take a sample of at least n = 50 to feel comfortable that your sample mean distribution is roughly normal. About This Article About...