Accuracy and precision
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Imagine you have the task to assess the mean height of students in a class. Unfortunately all you have for measuring the height is an old ruler, that has gotten a little longer with time. Thus, a bias is introduced by systematically overestimating the real height of each student. As a result the mean height for the whole class will also be too high. Here we say: the accuracy of mean height is low. | Imagine you have the task to assess the mean height of students in a class. Unfortunately all you have for measuring the height is an old ruler, that has gotten a little longer with time. Thus, a bias is introduced by systematically overestimating the real height of each student. As a result the mean height for the whole class will also be too high. Here we say: the accuracy of mean height is low. | ||
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Revision as of 08:30, 15 November 2010
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Hier gehts los...
Example:
- Accuracy:
Imagine you have the task to assess the mean height of students in a class. Unfortunately all you have for measuring the height is an old ruler, that has gotten a little longer with time. Thus, a bias is introduced by systematically overestimating the real height of each student. As a result the mean height for the whole class will also be too high. Here we say: the accuracy of mean height is low.
- Example:
- Precision:
Using a ruler (which varies its length due to bad manufacturing), you want to measure your own height. While measuring your height several times in a row, you recognize that you measure a different height with every measurement. The variation of each measurement around the mean height (your real height) gives you an idea about the precision of the measurement.
