Unit 4 sec 3.3
Mean versus median
11 December 2015
23:11
You might be thinking it is very well being told how to
calculate two different measures of location, but which should you use and
when? Well, it has already been suggested that there is no simple university applicable
answer to the question. But there are a few advantages and disadvantages of one
measure compared with the others.
In practice, both
the mean and median are widely used. They give similar results, but can
sometimes differ considerably. Typically, when the values of the dataset of the
two orders of one or other end of the range of values, there are large
differences between the mean and the median. For this reason, the median,
rather than the me tends to be used for summarising earnings. Where the values
are symmetrically spread, there will be little difference between the values of
the two summarises, in which case it will not matter much which one is chosen.
To sum up this
section, we have discussed summarising a dataset by measuring its location, is
a number that might be thought of as “average” “typical” or “central” value. Two
Particular measures of location were looked at in detail: the mean and the
median. The meaning of a set of numbers is found by adding all the numbers
together and dividing by how many numbers there are. To find the median, first
sort the data in order of size stop. If there is an odd number of data values,
the median is the middle value. If there is an even number of data values, the
media is defined as the mean of the middle two values. The mean and median are
two measures of location that were used as part of an initial study of the
probability words dataset. By comparing them, you were able to give support to
the notion that the word “probably” seems to indicate a higher degree of
likelihood than the words possible.
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