Which concept helps to describe the spread of data points around a central value?

The concept that helps to describe the spread of data points around a central value is variance. Variance measures how far each data point in a set is from the mean and thus from every other data point. It quantifies the degree of dispersion or spread in a distribution of data values. A high variance indicates that the data points are spread out over a wider range of values, while a low variance indicates that they are closer to the mean.

In contrast, the mean, median, and mode are measures of central tendency rather than measures of spread. The mean provides an average value, the median indicates the middle point of a data set, and the mode represents the most frequently occurring value. While these concepts are important for understanding the overall behavior of a data set, they do not convey how much the individual data points vary from the central value, which is crucial for assessing the spread of the data. Thus, variance is the correct choice for describing the spread of data points around a central value.