Which statistical measures are commonly used to analyze data distributions?

The correct answer encompasses a set of statistical measures that are fundamental in analyzing data distributions. Mean, mode, median, and standard deviation are key concepts in descriptive statistics used to summarize and describe the main features of a dataset.

The mean is the average of all data points and provides a central value. The median, which is the middle value when data points are arranged in order, offers insight into the dataset's center, especially useful for skewed distributions since it is not affected by outliers. The mode represents the most frequently occurring value in a dataset, giving an understanding of the most common data point.

Standard deviation measures the amount of variation or dispersion in a set of values. A low standard deviation signifies that data points tend to be close to the mean, whereas a high standard deviation indicates that data points are spread out over a wider range. Together, these measures provide a comprehensive picture of the shape and spread of the distribution, helping in making informed decisions based on data analysis.

Other options present valuable measures relevant for different analytical needs. However, they do not collectively cover the primary descriptive metrics for analyzing distributions like mean, mode, median, and standard deviation do. For instance, variance and range focus primarily on variability, while percentiles and quartiles (