Accuracy is how "correct" your answer is.
Precision is how "close" your answer is.
If you were to measure the amount of water your cup can hold:
An example of accuracy would be rounding numbers to significant figures.
Since there are uncertainties in the measurements you take, it would be more correct to use significant figures.
An example of precision would be the use of decimal places.
Although by using maths you can calculate the exact volume of the cup and give it correct to any number of decimal places, in reality, this is not always the case.
You can be precise without being accurate. In the above example, you can give a number with lots of decimal places, but it can be way off the actual answer.
You have two categories of data, accuracy and percision. accuracy is when a few values give an average of the true value. percision is when the few values are close to each other. Inaccurate however, is when the values average is not correct. In a less specific definition, an inaccuracy is something that is not factually correct
Q: differentiate between group and ungroup data
So accuracy is how close the mean is to the true value. Precision is how close all your values are to each other. If you have repeatable results you will see this straight away. Spiking samples with known amounts is a great way to find out if you have as much as you think you have i.e. checking the accuracy
Q: differentiate between group and ungroup data
Differentiate between Data Mining and Data Warehousing
In short, they do not. Relating tables in a database defines the relationships between the data sets in the different tables and allows the data to be accessed more efficiently, but it does not affect the accuracy of the data entered.
Numeric data are data that can be quantify. i.e age, e.t.c While Non-numeric data are data that cannot be quantify but can be categorise. Such as colour, name e.t.c
Secondary data is collected by someone other than the researcher, such as census information. Primary data is collected first hand, such as interviews.
C is statically typed. There is no need for dollar or percentage symbols to differentiate between character/string data and numeric data.
You can use different colors or symbols to differentiate between the different plots.
Differentiate shape data for information?
The precision of measurements affects the precision of scientific calculations by influencing the accuracy of the final result. More precise measurements lead to more accurate calculations as there is less uncertainty or variation in the data used for analysis. In contrast, less precise measurements can introduce errors and inaccuracies into the calculations.