The mean is a measure of central tendency because it provides a central value around which a set of data points is distributed. Specifically, the mean is calculated by summing all the values in a data set and then dividing by the number of values. This calculation gives a representation of what can be considered a typical value in the data set, making it useful for understanding the overall trend or average.
Central tendency measures, such as the mean, are essential for summarizing and conveying the essence of the data with a single value. They help in comparing different datasets and making inferences based on those datasets.
In contrast, standard deviation, range, and variance are all measures of variability or spread within a dataset. They describe how far the data points are from the mean or how widely dispersed the values are, but they do not provide a central value around which the data clusters. Therefore, the mean stands out as the clear measure of central tendency in this context.