when you are grading you can use the mean as an average.
The standard deviation of a distribution is the average spread from the mean (average). If I told you I had a distribution of data with average 10000 and standard deviation 10, you'd know that most of the data is close to the middle. If I told you I had a distrubtion of data with average 10000 and standard deviation 3000, you'd know that the data in this distribution is much more spread out. dhaussling@gmail.com
It is not enough to know only the mean or some other measure of the central tendency: it is useful to know the dispersion. If, in a test, the average score is 50 and you score 52 you have clearly scored better than average but how much better? If the scores range from 0 to 100, you are pretty close to average whereas if they range from 48 to 52 you are amongst the top of the class!
It is useful to know the name of a thing, but more useful to know the thing itself.
There is no meaningful average wen data are categorical (qualitative). Also, the arithmetic mean is not a good measure of central tendency when the data distribution is skewed.
Average is a casual word . You need to know the MEAN Mean = {10+12+14+16)/4 mean = 52/4 mean = 13 The answer!!!!
It is always useful to know about factors and multiples.
"Mean value" is another way of saying average.
Useful for...in a troop? Useful for...in a Circus? No offense, but what do you mean?
as useful as " is conduction or what part of speech it is?
abrar
The 'mean' is useful only if there is variability in the dataset, as it provides a central tendency that reflects the average of the values. In a dataset with no variability (where all values are identical), the mean becomes trivial, as it will simply equal that constant value. Therefore, the mean is most informative when it can summarize the distribution of diverse data points, highlighting trends and patterns within the variability.
this dick.. it keeps the average woman regular; if you know what I mean!