How do descriptive statistics and inferential statistics differ?

Descriptive statistics and inferential statistics serve different purposes in analysis and research. Descriptive statistics are designed to summarize and present data in a meaningful way, typically providing measures like means, medians, modes, standard deviations, and frequencies. Their main function is to describe the characteristics of a dataset, making it easier to understand and communicate findings about the data at hand.

On the other hand, inferential statistics go a step further by using sample data to make generalizations or inferences about a larger population. This involves estimating population parameters, testing hypotheses, and making predictions based on the sample data. For example, survey research often uses inferential statistics to conclude about a larger group based on the responses of a selected sample.

The distinction highlighted in the correct answer is crucial for understanding how researchers interpret and present their findings. Descriptive statistics provide the groundwork by summarizing data, while inferential statistics leverage that information to draw broader conclusions that can apply beyond the data collected.