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Accuracy and Precision

Accuracy and Precision. Measurements are qualitative or quantitative. Qualitative measurements give results that are descriptive and non-numerical. Example: Quantitative measurements give results that are definite, usually as numbers and units. Example:. Accuracy and Precision.

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Accuracy and Precision

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  1. Accuracy and Precision • Measurements are qualitative or quantitative. • Qualitative measurements give results that are descriptive and non-numerical. • Example: • Quantitative measurements give results that are definite, usually as numbers and units. • Example:

  2. Accuracy and Precision • Measurements work best when they are accurate and precise • Accuracy is a measure of how close a measurement comes to the actual or true value of whatever is measured. • To evaluate the accuracy of a measurement, it must be compared to the correct value. • Precision is a measure of how close a series of measurements are to one another. • The precision of a measurement depends on more than one measurement.

  3. Accuracy and Precision

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  5. Accuracy and Precision • In this picture, all of the darts land on the bulls-eye which illustrates good precision and accuracy. • In this picture, all of the darts land near each other, but away from the bulls-eye which illustrates good precision, but poor accuracy.

  6. Accuracy and Precision • Here the darts are not close to each other, but are close to the bulls-eye indicating poor precision, but good accuracy. • Finally, the darts are not close to each other or near the bulls-eye indicating both poor accuracy and poor precision.

  7. Accuracy and Precision • Sometimes there is a difference between the accepted value and the experimental value. • This difference is known as error. Error = accepted value – experimental value • Error can be positive or negative depending on whether the experimental value is greater than or less than the accepted value.

  8. Accuracy and Precision • Often it is useful to calculate relative error, or percent error. Percent error = error x100% accepted value • The percent error will always be a positive value.

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