Which statement best describes inferential statistics?

• A. Summarize data from a sample.
• B. Draw conclusions about a population using sample data.
• C. Always uses p-values.
• D. Only used for categorical data.

Answer: (B)

Inferential statistics are about using information from a sample to make statements about a larger group—the population—and to quantify how confident we are in those statements given sampling variability. The statement that captures this idea best is that we draw conclusions about a population using sample data, because that describes both the generalization and the uncertainty inherent in using only a subset of the population.

Descriptive statistics, by contrast, simply summarize the data we actually collected from the sample without extending those findings to a larger group. While p-values are a common tool in many inferential procedures, not every inferential analysis relies on them; methods based on confidence intervals or Bayesian approaches, for example, provide alternative ways to express uncertainty. And inferential techniques aren’t limited to categorical data; they apply to continuous, binary, ordinal, and other data types as well.