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The Difference Between Precision and Accuracy
When outlining the parameters of a project, striving for a close alignment with the genuine workload is crucial. The scope definition involves a collaborative process between you and the client to delineate and document specific project objectives encompassing features, functionalities, deliverables, deadlines, and overall project costs. Establishing the project scope serves as a cornerstone for resource allocation and effective time management throughout the project lifecycle. Both accuracy and precision find relevance in this context, particularly when gauging the magnitude of a project. Accuracy and precision, while both are definitions of measurement quality, they diverge significantly in their implications.
Accuracy pertains to the proximity of measurements to the true or accepted value. It reflects how close the recorded values are to the actual value being measured. On the other hand, precision relates to the consistency or repeatability of measurements. It underscores the extent to which successive measurements with the same instrument or process yield identical or highly similar results. In essence, accuracy denotes the fidelity of measurements, whereas precision underscores their replicability. Both factors play pivotal roles in determining the reliability and robustness of project-scoping endeavors.
- Precision relates to the consistency and reproducibility of measurements.
- Accuracy relates to the closeness of measurements to the true or accepted value.
It’s important to note that a measurement can be precise but not accurate (consistent but not close to the true value), accurate but not precise (close to the true value but not consistent), both precise and accurate (consistent and close to the true value), or neither precise nor accurate (neither consistent nor close to the true value). Achieving both precision and accuracy is ideal for high-quality measurements.
What is Accuracy?
Accuracy in measurements refers to the degree of closeness between the measured value and the true or accepted value of a quantity being measured. It reflects how well a measurement reflects reality or how close it is to the actual value being measured.
The ISO (International Organization for Standardization) uses a stricter definition. Accuracy refers to measurements that produce consistent and true results. An accurate measurement must have no systematic errors or random errors according to the ISO definition. The ISO recommends that precise be used when a measurement can be both exact and precise.
In essence, accuracy assesses the correctness, trueness, or validity of a measurement. A measurement is considered accurate when it is very close to the true value or the known standard value of the quantity being measured.
For example, if the actual length of an object is 10.0 centimeters, and after measurement, you consistently obtain values like 9.8 cm, 9.9 cm, and 10.1 cm, these measurements are accurate because they are very close to the true value, even though they might not be very precise due to slight variability.
Accuracy is crucial in various fields such as science, engineering, medicine, and industry, as it ensures that measurements are reliable and trustworthy. Achieving high accuracy is important for making informed decisions, ensuring quality control, and obtaining reliable data for research and development.
It’s important to note that while accuracy is vital, it doesn’t necessarily guarantee precision. A measurement can be accurate but not precise if it consistently hits near the true value but lacks consistency among repeated measurements. Accuracy and precision together indicate the overall quality and reliability of measurements.
What is Precision?
Precision in measurements refers to the degree of consistency, repeatability, or reproducibility of results when the same quantity is measured repeatedly under the same conditions. It assesses how closely individual measurements or values agree with each other. In essence, precision indicates the extent of scatter or variability among multiple measurements of the same quantity.
A measurement is considered highly precise when repeated trials or measurements yield very similar or closely clustered values. This suggests that there is minimal variability or deviation among the results, indicating a high level of consistency and reliability in the measurement process.
For instance, if you measure the length of an object multiple times and consistently obtain values like 10.1 cm, 10.0 cm, and 10.2 cm, the measurements are precise because they are very close to each other despite minor differences.
Precision is essential in various fields such as science, engineering, manufacturing, and statistics. It allows for reliable comparisons between different sets of measurements and ensures confidence in the consistency of the obtained data. However, it’s important to note that precision alone does not guarantee accuracy. A measurement can be precise but not accurate if the values consistently deviate from the true or accepted value, even though they are consistently close to each other.
Examples of Precision and Accuracy
A basketball player can be thought of as having precision and accuracy definitions. A high level of accuracy is demonstrated by a player who makes a basket every time, even though he hits different parts of the rim. He is precise if he makes fewer baskets but hits the same rim area every time. Players who make free throws that always go in the same direction achieve high levels of precision and accuracy.
A skilled archer consistently hits the bullseye with every arrow, and all the arrows are tightly grouped. In this case, the archer’s shots are both accurate (hitting the target) and precise (consistently hitting the same spot).
Experimental measurements are another example of precision or accuracy. Averaging can show you how close a collection of measurements is to the true value. You can measure the mass of a 51.0-gram sample to get values of 48.6, 48.6, and 48.5 grams. However, this scale is not very precise. Your average measurement is 48.6, which is lower than the true value. Your measurements were still consistent. Your scale should give you values of 50.9, 50.8, 51.5, and 52.0. However, it may not be as accurate as the first balance, but it will still be consistent. Although the average measurement is 51.2, there is a wider range of measurements. If you adjust for the error, a more precise scale is better to use in the laboratory. It is better to calibrate an exact instrument than to use an inaccurate, but accurate, one.
Accuracy, Precision, and Calibration
Is it better to have an accurate measurement recorder or one that is precise? The scale will be accurate if you have weighed yourself three times, and each time, the number is different but close to your true weight. However, it may be more accurate to use a scale that is precise even though it isn’t exact. This would mean that all measurements would be very close to one another, and the true value would be “off” by approximately the same amount. This is a problem with scales that often have a “tare button” to zero them.
Many instruments need calibration, even though scales and balances may allow you to adjust the accuracy or precision of measurements. A thermometer is an example. Thermometers are more reliable within a particular range but can give inaccurate, but not necessarily imprecise, values beyond that range. Record the deviations from true or known values when calibrating an instrument. To ensure accurate readings, keep a log of calibrations. To ensure precise and accurate readings, many pieces of equipment need to be calibrated periodically.
