我的理解是： accruracy: 是数据绝对准确，命中目标； 例句：A more accurate way to evaluate specificity would be to score the specificity levels individually starting from highest and moving on to lowest when necessary.
precision: 里面的cis是cut的意思，也即是提前砍掉周边的数据，剩下的数据是精准的， 没有一个参考的目标值。 例句： About their methods, however, we can be much more precise.
下面是原文：
Accuracy and Precision: Definition, Examples
Accuracy and Precision
You can never make exact measurements in an experiment (even the atomic clock isn’t exact: it loses a second every 15 billion years). How far away from the “mark” you are is described by accuracy and how well you measure is described by precision.
Accuracy
Accuracy is how close you are to the true value. For example, let’s say you know your true height is exactly 5’9″.
You measure yourself with a yardstick and get 5’0″. Your measurement is not accurate.
You measure yourself again with a laser yardstick and get 5’9″. Your measurement is accurate.
Note: The true value is sometimes called the theoretical value.
Precision
Precision is how close two or more measurements are to each other. If you consistently measure your height as 5’0″ with a yardstick, your measurements are precise.
Accuracy of Analysis and Precision Together
If you are precise, that doesn’t necessarily mean you are accurate. However, if you are consistently accurate, you are also precise.
“More” Precise
If you want to tell which set of data is more precise, find the range (the difference between the highest and lowest scores). For example, let’s say you had the following two sets of data:
Sample A: 32.56, 32.55, 32.48, 32.49, 32.48.
Sample B: 15.38, 15.37, 15.36, 15.33, 15.32.
Subtract the lowest data point from the highest:
Sample A: 32.56 – 32.48 = .08.
Sample B: 15.38 – 15.32 = .06.
Sample B has the lowest range (.06) and so is the more precise.
