Overview
This lecture explains the difference between accuracy and precision in measurements, using both visual and numerical examples.
Accuracy vs. Precision
- Accuracy describes how close measurements are to the accepted or true value.
- Precision describes how close measurements are to each other, regardless of their closeness to the true value.
- A data set can be precise without being accurate, or accurate without being precise.
Visual Example
- Hitting the bullseye on a target with all shots close together is both accurate and precise.
- Hitting the same area away from the bullseye with all shots close together is precise but not accurate.
Numerical Example: Density of Silver
- Accepted value for silver’s density: 10.5 g/cm³.
- Group A: Average measurement = 10.8 g/cm³, close to the correct value; thus, Group A is more accurate.
- Group A’s individual measurements vary greatly, showing low precision.
- Group B: Average measurement = 13.2 g/cm³, far from correct value; not accurate.
- Group B’s measurements are close to each other, indicating high precision.
Key Terms & Definitions
- Accuracy — closeness of measurements to the accepted or true value.
- Precision — closeness of measurements to each other, regardless of the true value.
Action Items / Next Steps
- Practice distinguishing accuracy and precision using sample data sets.
- Review textbook sections on measurement reliability.