Bimodal Distribution vs Uniform Distribution
Both terms below come up in the same part of the course, and students mix them up. Here is each one defined on its own, side by side, so you can see where they part company.
Bimodal distribution
Describing data
A bimodal distribution has two distinct peaks, showing two values or ranges where observations cluster most heavily.
A bimodal shape has two clear humps, which often signals that the data mix two different groups. For example, heights measured from a room of both children and adults may peak once near each group's typical height. Each peak is a mode, so two peaks means two modes, in contrast to a single-peaked (unimodal) distribution. When you see two modes, it is worth asking whether the data should be split into subgroups.
Uniform distribution
Describing data
A uniform distribution is one in which every outcome or interval of equal size is equally likely, giving a flat shape.
In a uniform distribution the graph is level because no value is favored over another. For example, rolling a fair six-sided die gives each face a probability of . For a continuous uniform distribution on an interval, the density is constant and probability equals the fraction of the interval covered. A flat dotplot or histogram is the visual signature of uniformity.