Unit 4 - Precision of Data
In this GCSE Biology quiz we look at precision of data. Precision is a measure of repeatability or reproducibility of scientific measurements. It is the degree to which repeated measurements, under the same experimental conditions, give the same result.
Accuracy is not the same thing as precision. Accuracy is about measurements being as close to the true value as possible. Precision is the measurement being the same value each time the experiment is performed. A measurement system can be accurate but not reliable (precise) or vice versa.
Precision is written as a percentage. It tells you how precisely you can use a piece of equipment to take a reading. It is calculated by subtracting the maximum percentage error from 100%.
Take for example a balance that is set to read in grams. If you take a reading of 10 grams, it could in fact be anywhere between 9.5 and 10.5 grams. That is one gram difference on the reading of 10 grams - that is a 10% error so in this case, the precision of the reading would be 100% minus 10% i.e. 90% precision.
If the balance is now set to read in tenths of a gram, a reading of 10 grams could be as low as 9.9 grams or as high as 10.1 grams. The error could be plus or minus 0.1 grams. Now this is only a total of two hundredths (i.e. 2%) of the 10 gram reading so the precision is now 100% minus 2% or 98% precision.
Precision is also applied in a similar way to a set of results or data. You first work out the mean value. Then you take the difference between the lowest and highest result and calculate it as a percentage of the mean value. Subtract that from 100% to find the precision of the experiment.
Precise measurements are ones in which there is very little spread about the mean value. Precision depends only on the extent of random errors which is why it gives no indication of how close the results are to the true value and is not a measure of accuracy.
Is it precise results or accurate ones which can be repeated? Try this quiz see how well you understand the precision of data.
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