Precision is a number that shows an amount of the information digits and it expresses the value of the number. For Example- The appropriate value of pi is 3.14 and its accurate approximation. But the precision digit is 3.199 which is less than the exact digit.

Exact numbers are either defined numbers or the result of a count. For example, a dozen is defined as 12 objects, and a pound is defined as 16 ounces. An exact number can only be expressed in one way and cannot be simplified any further. Counted numbers are exact: there are two chairs in the photograph.

9. Speed of light in a vacuum is exact, and is equal to 299,792,458 m/s….Exact Numbers.

5. “Percent” means out of exactly one hundred. e.g. 25.9% means 25.9 out of exactly 100 or 25.9/100 (25.9 has 3 sig. fig., but 100 is exact.)

The term average is the little sign that you go out that tells you that this is a not exact number because average means that every single person in the school has different height and this is just taking the average.

Rule: When we add or subtract numbers, we should round the result to the same number of decimal places as the number with the least number of decimal places (i.e., the least precise value in terms of addition and subtraction).

In mathematics, precision describes the level of exactness in a number’s digits, such as number 54.6 having precision 1 (one decimal digit). A number with end zeroes (“00”) has a negative precision, such as 500 having precision -2, or 4,000 as precision -3.

a number that is precise but not accurate: 99999.12345678901234567890 . That’s much more precise since it conveys more information. Unfortunately its accuracy is way off since it’s nowhere near the target value. a number that is both accurate and precise: 3.142857143 .

calculated value will have the same number of digits to the right of the decimal point as that of the least precise quantity. In practice, find the quantity with the fewest digits to the right of the decimal point. In the example below, this would be 11.1 (this is the least precise quantity).

Example 2. Rule: When we add or subtract numbers, we should round the result to the same number of decimal places as the number with the least number of decimal places (i.e., the least precise value in terms of addition and subtraction).

Archer X

Precision is a metric that quantifies the number of correct positive predictions made. Precision, therefore, calculates the accuracy for the minority class. It is calculated as the ratio of correctly predicted positive examples divided by the total number of positive examples that were predicted.

Explanation: When combining values with different degrees of precision, the precision of the final answer can be no greater than the least precise measurement. However, it is a good idea to keep one more digit than is significant during the calculation to reduce rounding errors.

The precision of a measuring tool is related to the size of its measurement increments. The smaller the measurement increment, the more precise the tool. When adding or subtracting measured values, the final answer cannot contain more decimal places than the least precise value.

That is, a good F1 score means that you have low false positives and low false negatives, so you’re correctly identifying real threats and you are not disturbed by false alarms. An F1 score is considered perfect when it’s 1 , while the model is a total failure when it’s 0 .

If you get a large f value (one that is bigger than the F critical value found in a table), it means something is significant, while a small p value means all your results are significant. The F statistic just compares the joint effect of all the variables together.

Accuracy is used when the True Positives and True negatives are more important while F1-score is used when the False Negatives and False Positives are crucial. In most real-life classification problems, imbalanced class distribution exists and thus F1-score is a better metric to evaluate our model on.