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The Internet has many places to ask questions about anything imaginable and find past answers on almost everything.
Emphatic order asks you to organize your paper in the order of how strong your examples are (hence the word “emphatic” or placing emphasis on certain information over other pieces of information based upon importance).
Quick: What’s the most emphatic part of a sentence?…CAREFUL WITH TYPEFACE
An emphatic assertion occurs when the speaker or writer conveys sympathy or recognition of the other person’s position or feelings. This acknowledgement is then followed by a statement that conveys the speaker’s own beliefs.
(1) It’s impossible to be accurate about these things. (2) She gave an accurate account of the case. (3) The figures they have used are just not accurate. (4) His account of what happened is substantially accurate.
Here are 4 tips that should help you perfect your pronunciation of ‘accurate’:
It is correct to use “more accurate” . You can have more and less accurate. It is the closeness to a target.
: very accurate and exact. —used to refer to an exact and particular time, location, etc. : very careful and exact about the details of something. See the full definition for precise in the English Language Learners Dictionary.
In simpler terms, given a set of data points from repeated measurements of the same quantity, the set can be said to be accurate if their average is close to the true value of the quantity being measured, while the set can be said to be precise if the values are close to each other.
10 Techniques for More Precise Writing
Precision refers to how close measurements of the same item are to each other. Precision is independent of accuracy. That means it is possible to be very precise but not very accurate, and it is also possible to be accurate without being precise. The best quality scientific observations are both accurate and precise.
Accuracy and Precision Measurements can be both accurate and precise, accurate but not precise, precise but not accurate, or neither. High accuracy, low precisionOn this bullseye, the hits are all close to the center, but none are close to each other; this is an example of accuracy without precision.
Accuracy refers to how close measurements are to the “true” value, while precision refers to how close measurements are to each other.
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.
Find the difference (subtract) between the accepted value and the experimental value, then divide by the accepted value. To determine if a value is precise find the average of your data, then subtract each measurement from it.
Accuracy is how close a value is to its true value. An example is how close an arrow gets to the bull’s-eye center. Precision is how repeatable a measurement is. An example is how close a second arrow is to the first one (regardless of whether either is near the mark).
A precision of 75% means 75% of the times the detector went off, they were actually positive cases. The problem with a low precision score is spending time having people undergo further screenings or using medication unnecessarily.
While precision refers to the percentage of your results which are relevant, recall refers to the percentage of total relevant results correctly classified by your algorithm. Unfortunately, it is not possible to maximize both these metrics at the same time, as one comes at the cost of another.
A binary classification task. Clearly, the higher the F1 score the better, with 0 being the worst possible and 1 being the best.
For example, a perfect precision and recall score would result in a perfect F-Measure score:
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 .
Recall is the number of relevant documents retrieved by a search divided by the total number of existing relevant documents, while precision is the number of relevant documents retrieved by a search divided by the total number of documents retrieved by that search.
Recall is more important than precision when the cost of acting is low, but the opportunity cost of passing up on a candidate is high.