Density probability plots compare two different ways of estimating the shape of a set of data. One way is by assuming the data follows a specific type of distribution, like a bell curve or exponential curve. The other way is by using the actual data points to estimate the distribution. If the assumed distribution matches the actual data well, the two estimates will be similar. These plots are useful for understanding how well a chosen distribution fits the data. The researchers compared these plots with other common methods like histograms and quantile-quantile plots using both simulated and real data.