The article compares two methods, distributional regression (DR) and quantile regression (QR), for estimating the relationship between a random variable and a set of variables. DR estimates the distribution of the variable, while QR estimates specific quantiles. The study shows that both methods can be used to estimate the relationship accurately, especially in linear models and certain types of models with varying levels of variability.