What is the purpose of descriptive statistics?

Descriptive statistics serves the purpose of summarizing and providing insights into a dataset. It focuses on presenting the main characteristics of the data in a clear and understandable manner, often through measures such as means, medians, modes, and standard deviations, along with visual representations like graphs and charts. This allows researchers and decision-makers to quickly grasp key features of the data, identify patterns, and communicate findings effectively without necessarily making inferences beyond the data at hand.

The other options involve different aspects of statistical analysis. For instance, making inferences about a population is related to inferential statistics, which uses sample data to draw conclusions about a larger group. Testing hypotheses also falls under inferential statistics, where researchers assess the validity of a presumed relationship or effect based on sample data. Predicting future outcomes relates to predictive analytics and modeling, which aims to forecast future events based on current data trends. In contrast, descriptive statistics is fundamentally about providing a clear picture of the existing data rather than going beyond to make predictions or inferences.