# LOG#078. Averages. I am going to speak a little bit about Statistics. The topic today are “averages”. Suppose you have a set of “measurements” where . Then you can define the following quantities:

Arithemtic mean. Geometric mean. Harmonic mean. Remark: In the harmonic mean we need that every measurement is not null, i.e., Remark (II): There are some other interesting “averages”/”means”: Generalized p-th mean. Weighted mean/average. where are the weight functions and they satisfy A particularly important case occurs when the weight equals to inverse of the so-called variance of a population with finite size (generally denoted by ), i.e.,  when , the weighted mean yields: Midrange.

Finally, a “naive” and usually bad statistical measure for a sample or data set is the midrange. Really, it is a mere measure of central tendency and no much more: Here, refer to the maximum and minimum value of the sampled variable x in the full data set .

Many of the above “averages” have their own relative importance in the theory of Statistics. But that will be the topic of a future blog post handling statistics and its applications.

What average do you like the most? Are you “on the average”? Are you “normal”? 😉 Of course, you can consult your students, friends or family if they prefer some particular mean/average over any other in their grades/cash sharing, or alike :).

See you soon in other blog post!

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