File Name: accuracy and precision in measurement .zip
Accuracy and precision are two important factors to consider when taking data measurements. Both accuracy and precision reflect how close a measurement is to an actual value, but accuracy reflects how close a measurement is to a known or accepted value, while precision reflects how reproducible measurements are, even if they are far from the accepted value. You can think of accuracy and precision in terms of hitting a bull's-eye.
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Accuracy is how close a measurement is to the correct value for that measurement. The precision of a measurement system is refers to how close the agreement is between repeated measurements which are repeated under the same conditions. Measurements can be both accurate and precise, accurate but not precise, precise but not accurate, or neither. All measurements are subject to error, which contributes to the uncertainty of the result.
Errors can be classified as human error or technical error. Technical error can be broken down into two categories: random error and systematic error. Random error, as the name implies, occur periodically, with no recognizable pattern. Systematic error occurs when there is a problem with the instrument. For example, a scale could be improperly calibrated and read 0.
All measurements would therefore be overestimated by 0. Unless you account for this in your measurement, your measurement will contain some error. The random error will be smaller with a more accurate instrument measurements are made in finer increments and with more repeatability or reproducibility precision. Consider a common laboratory experiment in which you must determine the percentage of acid in a sample of vinegar by observing the volume of sodium hydroxide solution required to neutralize a given volume of the vinegar.
You carry out the experiment and obtain a value. Just to be on the safe side, you repeat the procedure on another identical sample from the same bottle of vinegar.
If you have actually done this in the laboratory, you will know it is highly unlikely that the second trial will yield the same result as the first. In fact, if you run a number of replicate that is, identical in every way trials, you will probably obtain scattered results. With multiple measurements replicates , we can judge the precision of the results, and then apply simple statistics to estimate how close the mean value would be to the true value if there was no systematic error in the system.
Boundless vets and curates high-quality, openly licensed content from around the Internet. This particular resource used the following sources:. Skip to main content. Introduction to Chemistry. Search for:. Accuracy, Precision, and Error. Learning Objective Describe the difference between accuracy and precision, and identify sources of error in measurement. Precision expresses the degree of reproducibility or agreement between repeated measurements. The more measurements you make and the better the precision, the smaller the error will be.
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3.12: Accuracy and Precision
In a set of measurements, accuracy is closeness of the measurements to a specific value, while precision is the closeness of the measurements to each other. Precision is a description of random errors , a measure of statistical variability. In simpler terms, given a set of data points from repeated measurements of the same quantity, the set can be said to be accurate if their average is close to the true value of the quantity being measured, while the set can be said to be precise if the values are close to each other. In the first, more common definition of "accuracy" above, the two concepts are independent of each other, so a particular set of data can be said to be either accurate, or precise, or both, or neither. In the fields of science and engineering , the accuracy of a measurement system is the degree of closeness of measurements of a quantity to that quantity's true value. The field of statistics , where the interpretation of measurements plays a central role, prefers to use the terms bias and variability instead of accuracy and precision: bias is the amount of inaccuracy and variability is the amount of imprecision. A measurement system can be accurate but not precise, precise but not accurate, neither, or both.
In fact, I even remembered using the words interchangeably in my writing for English class! However, as I continued through more advanced science and math courses in college, and eventually joined Minitab Inc. So what types of measurement system errors may be taking place? Accuracy refers to how close measurements are to the "true" value, while precision refers to how close measurements are to each other. Repeatability : The variation observed when the same operator measures the same part repeatedly with the same device. Reproducibility : The variation observed when different operators measure the same part using the same device. A dart board can help us visualize the difference between the two concepts:.
Accuracy and precision
Basketball is one of those sports where you need to hit a target. A football field goal kicker might have room for some deviation from a straight line - for college and pro football there is an 18 foot 6 inch space for the ball to go through. In basketball, the basket is only 18 inches across and the ball is a little less than 10 inches across - not much room for error. The ball has to be on target in order to go into the basket and score.