Which statement correctly differentiates descriptive statistics from inferential statistics?

• A. Descriptive describes the sample; inferential generalizes to the population and tests hypotheses.
• B. Descriptive describes hypotheses; inferential describes the sample.
• C. Descriptive measures central tendency; inferential measures variability.
• D. Descriptive and inferential are identical.

Answer: (A)

Descriptive statistics focus on summarizing and describing the data you have from a sample—things like the average, middle value, spread, and overall shape. Inferential statistics take those sample results and use them to make judgments about a larger population, often through estimating population parameters and testing hypotheses. The statement that descriptive describes the sample and inferential generalizes to the population and tests hypotheses captures this difference: descriptive tools summarize what you’ve collected, while inferential tools extend those findings beyond the sample to make inferences and evaluate ideas about the broader group. For example, you might report the class average and standard deviation to describe the class, but you’d use inferential statistics to decide if that class average represents the school's or district’s average and to test whether it differs from a known value. The other options mix up roles (describing hypotheses or the sample), confound what descriptive versus inferential statistics measure, or claim they are the same, which obscures the true distinction.