What statistical method is often used to visualize the distribution of data?

The box plot is a powerful statistical tool for visualizing the distribution of data. It effectively summarizes key characteristics such as the median, quartiles, and potential outliers within a dataset. The visual representation allows for an immediate understanding of the central tendency and variability.

In a box plot, the central box represents the interquartile range (IQR), which contains the middle 50% of the data, while the line within the box indicates the median. The "whiskers" extending from the box show the range of the data, and individual points outside of this range can be identified as outliers. This concise display makes it easy to compare distributions across different groups or datasets, providing insights into their shapes, center locations, and spread.

Other options, such as pie charts or line graphs, serve different purposes—like showing proportions or trends over time—while bar graphs typically compare categorical data. However, none of these provide the same level of detail regarding distributional characteristics as the box plot does. Thus, the box plot is the appropriate choice when tasked with visualizing the distribution of data.