What describes the first step in measuring central tendency for a dataset?

The first step in measuring central tendency for a dataset is to sort the data. Sorting the data allows for better organization and understanding of the distribution of values within the dataset. By arranging the data, you can more easily identify key characteristics, such as the minimum, maximum, median, mode, or any patterns that may exist.

Sorting provides a foundational framework for calculating various measures of central tendency subsequently. For example, once the data is sorted, identifying the median becomes a straightforward task as it is the middle value in an ordered dataset. Similarly, finding the mode or computing the mean can be done more effectively with the data in a sorted format.

The other options, such as calculating the sample size, finding the mode, and computing the mean, are indeed important steps in data analysis but are typically performed after the initial sorting process. Understanding the layout of the data first enables more accurate and meaningful calculations of central tendency.