Using the 5 Number Summary
Statistical calculators apply quantitative methods to summarize data, test hypotheses, and quantify uncertainty. Understanding the output in context — not just the number — is what makes statistics useful.
Key questions before interpreting results
- Is the sample size large enough for the result to be reliable? Small samples produce unreliable estimates even with correct formulas.
- Is the underlying distribution appropriate for the method being used? Many statistics assume normality or independence.
- What is the practical significance alongside statistical significance? A statistically significant difference can be too small to matter in practice.
Communicating results
Always report results with their context: the sample size, the confidence level, and the measure used. A result of "p = 0.04" means nothing without knowing the test performed, the sample, and whether the test was pre-registered or exploratory.
Frequently Asked Questions
How accurate are the results?
The 5 Number Summary applies a standard formula to your inputs — accuracy depends on how precisely you measure those inputs. For planning and estimation, results are reliable. For high-stakes or professional decisions, cross-check the output with a domain expert or primary source.
What sample size do I need for reliable results?
It depends on the desired confidence level, margin of error, and population variance. For a typical survey (95% confidence, ±5% margin), n ≈ 385 for a large population. Smaller samples are fine for exploratory analysis, but don't over-interpret the results — widen your confidence intervals to reflect the uncertainty.