In research, how are descriptive statistics primarily used?

Descriptive statistics serve the crucial role of summarizing and describing key features of a dataset. This involves providing insights into the general characteristics and tendencies within the data, such as measures of central tendency (mean, median, mode) and measures of variability (range, variance, standard deviation). By using descriptive statistics, researchers can effectively communicate the essential aspects of the dataset they are analyzing without making assumptions or predictions about what the data may indicate in the future. This foundational step is critical in research as it lays the groundwork for further analysis and interpretations.

The other choices reflect functionalities that are outside the primary role of descriptive statistics. Making predictions pertains more to inferential statistics, which use sample data to infer conclusions about a larger population. Comparing different datasets typically involves the use of inferential statistics or comparison tests, while the decision to discard outliers is often a methodological choice that can affect the overall analysis and is not a main function of descriptive statistics.