A statistician says that scientific statements have to be very precise and we ha
ID: 3201881 • Letter: A
Question
A statistician says that scientific statements have to be very precise and we have to think hard about whether they are true. This can lead to discussions about: How precise is "very" precise? Should we say e.g., that the mean height of US men is 5'10" or would it be more "scientific" to say that it is 5'10.23416"? Please explain in 2 paragraphs. A statistician says that scientific statements have to be very precise and we have to think hard about whether they are true. This can lead to discussions about: How precise is "very" precise? Should we say e.g., that the mean height of US men is 5'10" or would it be more "scientific" to say that it is 5'10.23416"? Please explain in 2 paragraphs.Explanation / Answer
Precision refers to the closeness of two or more measurements to each other. As an example , if you weigh a given substance five times, and get 3.2 kg each time, then your measurement is very precise. Precision is independent of accuracy. You can be very precise but inaccurate.
A good analogy for understanding accuracy and precision is to imagine a basketball player shooting baskets. If the player shoots with accuracy, his aim will always take the ball close to or into the basket. If the player shoots with precision, his aim will always take the ball to the same location which may or may not be close to the basket. A good player will be both accurate and precise by shooting the ball the same way each time and each time making it in the basket.
Take experimental measurements for another example of precision and accuracy. If you take the measurements of the mass of a 50.0-gram standard sample and get values of 47.5, 47.6, 47.5, and 47.7 grams, your scale is precise, but not very accurate. If your scale gives you values of 49.8, 50.5, 51.0, 49.6, it is more accurate than the first balance, but not as precise. The more precise scale would be better to use in the lab, providing you made an adjustment for its error.
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