Which feature of PROC UNIVARIATE provides visual insights about data distribution?

PROC UNIVARIATE is a powerful procedure in SAS that offers various features for the analysis of univariate data, including descriptive statistics and graphical representations. The feature that provides visual insights about data distribution is the histogram fitted with probability density curves.

Histograms are graphical representations that display the frequency distribution of a dataset. They allow analysts to see how data points are spread across different value ranges. By fitting a probability density curve to the histogram, one can visualize the overall shape of the data distribution. This fitted curve helps to identify patterns in the data, such as normality, skewness, or the presence of multimodal characteristics (multiple peaks).

Additionally, presenting data in this combined visual manner allows for a clearer interpretation of potential underlying distributions, facilitating better decision-making in statistical analyses. The probability density curve enhances the histogram, providing a continuous estimation of the probability of occurrences, thereby offering a richer understanding of the data's behavior.

While other options like text-based summaries, standard deviation tables, and box-and-whisker plots offer valuable information, they do not provide the same level of visual insight into the distribution characteristics of the dataset as the histogram fitted with probability density curves.