Observational classification is based on what you see and observe about the thing (maybe during an experiment) While theoretical classification is based on what you are being taught or what you have been taught or what you read about the thing.
difference between knowledge classification and book classification?
in an experiment, the researcher manipulates a variable
There is only a slight difference between discrimination and classification in data mining. Discrimination can be negative and classification is generally just factual.
In an experiment, the researcher manipulates a variable.
Empirical anything is what is observed. Theoretical is a calculation of what things ought to be.
To find the percent difference between an experimental value and a theoretical value, first calculate the absolute difference by subtracting the theoretical value from the experimental value. Then, take the absolute value of this difference. Next, divide the absolute difference by the theoretical value, and finally multiply the result by 100 to convert it into a percentage. The formula is: (\text{Percent Difference} = \left( \frac{|\text{Experimental} - \text{Theoretical}|}{|\text{Theoretical}|} \right) \times 100).
data classification in statistics
Modern classification is based on evolutionary relationships between organisms while traditional classification is not.
Classification is sorting out things due to scientific process. Partition is eminent domain.
A question is a question. A hypothesis is a theoretical answer, but one which has not been tested.
so scientists can tell the difference between animals
empirical probability is when you actually experiment with it and get data values, and theoretical probability is when you use math to make an educated guess.