In dentistry: SD helps interpret consistency—e.g., variation in probing depth reduction across patients after treatment.
Real Dental Scenario
Comparing pocket depth consistency between two clinics
Scenario: Two dental clinics measured periodontal pocket depths (mm) for 5 patients each. Which clinic shows more consistent treatment outcomes?
Clinic A (Consistent)
Clinic B (Variable)
1 Calculate the Means
2 Deviations from the Mean
Clinic A deviations
Clinic B deviations
3 Standard Deviation Results
4 Visual Comparison of Spread
Clinical Interpretation
Clinic A: Low SD (0.39 mm)
Consistent outcomes. Patients receive predictable treatment quality. Good for standardized protocols.
Clinic B: High SD (1.87 mm)
Highly variable outcomes. Some patients have shallow pockets (2.0), others have deep ones (7.0). Needs investigation.
Key Takeaway: The mean alone does not tell the full story. A small SD means reliable, consistent treatment results. A large SD signals inconsistency that may require clinical review.
Interactive: see SD change
Adjust the spread slider to generate different "pocket depth" samples and observe how SD affects the histogram.
Histogram of measurements
Wider distributions reflect larger SD; tight clustering reflects small SD.
How to report SD (common patterns)
- Use mean ± SD when the data are reasonably symmetric.
- If the distribution is very skewed/outlier-heavy, prefer median (IQR).
- Compare SDs across groups to discuss variability, not just center.