Which statement correctly describes descriptive versus inferential statistics?

• A. Descriptive statistics summarize data; inferential statistics draw conclusions about a population from samples.
• B. Descriptive statistics test hypotheses; inferential statistics describe data.
• C. Descriptive statistics are only qualitative; inferential are quantitative.
• D. Descriptive statistics predict future values; inferential statistics measure reliability.

Answer: (A)

The difference being tested is between simply describing data and using data to make inferences about a larger group. Descriptive statistics are about summarizing what the data show—measures like the average, median, mode, range, and variability. Inferential statistics go a step further: they use information from a sample to make conclusions about a population from which the sample came, such as estimating a population mean or testing whether a difference is likely not due to chance.

For example, if you have exam scores from a class, descriptive statistics would tell you the class average and how spread out the scores are. If you want to make a statement about all students who took the test, you’d use inferential statistics to infer the population mean or to test hypotheses about differences.

The other statements mix up these roles: descriptive statistics do more than test hypotheses; that’s the realm of inferential statistics. Saying descriptive statistics are only qualitative and inferential are only quantitative is incorrect because descriptive stats can be either qualitative or quantitative, and inferential stats are not defined by being qualitative or quantitative. Finally, predicting future values or measuring reliability aren’t what defines descriptive versus inferential: prediction is a forecasting task, and reliability relates to consistency of measurement, not the core distinction between describing data and drawing population-level conclusions.