What is the difference between descriptive and inferential statistics in educational research?

• A. Descriptive is qualitative; inferential is quantitative.
• B. Descriptive summarizes data; inferential uses sample data to generalize about a population.
• C. Descriptive estimates population parameters; inferential summarizes data.
• D. Descriptive tests hypotheses; inferential describes data.

Answer: (B)

Descriptive statistics describe the data you collected in your study. They summarize what happened in the sample with numbers and simple measures—like the average score, the spread of scores, or the frequency of each category—so you can see the overall picture of your dataset. It’s all about the data you have, with no claims beyond that group.

Inferential statistics, on the other hand, use the data from your sample to make informed guesses about a larger population. They involve estimating population parameters (such as the true mean) and testing ideas (like whether two teaching methods differ) while accounting for sampling error. This is where confidence intervals and hypothesis tests come in, because you’re extending conclusions beyond the observed sample.

So the best description is that descriptive statistics summarize data, while inferential statistics use sample data to generalize about a population. The other statements misstate these roles—for example, descriptive statistics aren’t limited to qualitative data, and inferential statistics, not descriptive, are used for estimating parameters and testing hypotheses.