Table of Contents
Precision
Return to accuracy, Precision vs. Accuracy
Precision
Precision refers to the degree to which repeated measurements or calculations of a quantity yield the same or similar results. It is a measure of consistency and reproducibility, indicating how consistently a measurement or calculation can be repeated under the same conditions.
Characteristics of Precision
- Consistency: Precision reflects the ability to obtain consistent results over multiple trials or measurements. For example, if a scale repeatedly measures the weight of an object as 50 grams with minimal variation, it is considered precise.
- Repeatability: In practice, precision is assessed through repeatability, which involves conducting multiple measurements or calculations and comparing the results. High precision indicates that the values are close to each other, regardless of their proximity to the true value.
Precision vs. Accuracy
- High Precision, Low Accuracy: For example, a thermometer that consistently reads 99.5°C when the true temperature is 100°C exhibits high precision but low accuracy.
Importance of Precision
- Scientific Research: Precision is crucial in scientific research and experiments where consistent results are needed to validate hypotheses and theories. It ensures that experimental outcomes are reliable and reproducible.
- Quality Control: In manufacturing and quality control, precision helps maintain product consistency and meet specifications. High precision in measurements ensures that products conform to design standards and operational requirements.
Measuring Precision
- Statistical Measures: Precision can be quantified using statistical measures such as standard deviation and variance. These metrics assess the spread of data points around the mean, providing insights into the level of precision.
- Instruments: The precision of measuring instruments is often specified in their technical documentation. Instruments with high precision have small tolerances and can produce closely grouped measurements.
References and Further Reading
- Snippet from Wikipedia: Accuracy and precision
Accuracy and precision are two measures of observational error. Accuracy is how close a given set of measurements (observations or readings) are to their true value. Precision is how close the measurements are to each other.
The International Organization for Standardization (ISO) defines a related measure: trueness, "the closeness of agreement between the arithmetic mean of a large number of test results and the true or accepted reference value."
While precision is a description of random errors (a measure of statistical variability), accuracy has two different definitions:
- More commonly, a description of systematic errors (a measure of statistical bias of a given measure of central tendency, such as the mean). In this definition of "accuracy", the concept is independent of "precision", so a particular set of data can be said to be accurate, precise, both, or neither. This concept corresponds to ISO's trueness.
- A combination of both precision and trueness, accounting for the two types of observational error (random and systematic), so that high accuracy requires both high precision and high trueness. This usage corresponds to ISO's definition of accuracy (trueness and precision).