Dorin Mărghidanu
Corabia, Olt, România
Correspondence to: Dorin Mărghidanu, Corabia, Olt, România.
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Copyright © 2020 The Author(s). Published by Scientific & Academic Publishing.
This work is licensed under the Creative Commons Attribution International License (CC BY).
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Abstract
The purpose of this note is to present a relation between the arithmetic mean, of a finite number of real numbers, and the arithmetic mean of their images through a convex function. Some applications of this inequality are also included.
Keywords:
Arithmetic mean, Convex function, Jensen inequality
Cite this paper: Dorin Mărghidanu, An Inequality between the Arithmetic Mean of Some Numbers and the Arithmetic Mean of Their Images through a Convex Function, Modern International Journal of Pure and Applied Mathematics, Vol. 4 No. 1, 2020, pp. 1-4. doi: 10.5923/j.mijpam.20200401.01.
1. Introduction
Let
be a fixed natural number, and
an interval of real numbers. For every
, the arithmetic mean associated to
is defined as:
Let
be an interval. If
is a convex (concave) function, then the well known Jensen inequality (see [2]-[4], [10], [11] says that:
which can be written, using the above notation, as: | (1.1) |
The inequality (1.1) represents a relation between the image of
, through
, and the arithmetic mean of the images of the numbers
We can imagine the numbers
as being some data
received by a statistician. For large values of
, it is hard for the statistician to look at each number,
in these data. So, the statistician decides to make a skeleton of the data, composed of the minimum
and maximum
values of these data, a center
of the data, and a number
measuring the spread of the data. While
and
are easy to define as: | (1.2) |
and | (1.3) |
there are many different ways to define the center
. One very popular way is to a apply first a strictly monotone function
to the data
, obtaining the new data
. Then we compute the average value
, defined as: | (1.4) |
 | (1.5) |
Finally, we apply the inverse function
to
, defining the center of the data to be: | (1.6) |
A typical example of such functions, used in computing the center of data consisting of positive numbers, is given by the functions:
, for
. Following the above procedure, these functions give rise to the H¨older means of the positive numbers
Because different functions
and
produce different centers
and
of the data, it is important to find inequalities relating
and
in order to understand the inequalities between
and
.
2. Main Result
We present now the result leading to the main result of this note.Proposition 2.1 If1.
is a convex (concave) function;2.
, for all
, where
then the following inequality: | (2.7) |
holds.Proof. Let
be fixed. Since
can be written as the following convex combination of
and 
If we denote
and
, then since
, and
we conclude from the definition of convexity of
, that: | (2.8) |
Summing up in the last inequality from
we obtain:
After multiplying both sides of the last relation by
we obtain:
which is equivalent to:
If
is concave all the inequalities from this proof are reversed.Corollary 2.2. If we impose the additional condition that
to the assumptions from Proposition 2.1, then: | (2.9) |
Proof. Since
, we have
. Dividing both sides of the inequality (2.7) by the strictly positive number
, we obtain (2.9).Theorem 2.3 Let
be real numbers,
and
. Let
and
, be two strictly increasing and bijective functions, such that:
is convex on
. Then: | (2.10) |
Proof. We apply Proposition 2.1 to the numbers:
and the convex function
obtaining inequality (2.10).Application 2.4 Let
It is clear that
is convex and strictly increasing on
. Thus for all
, such that
, we conclude from (2.9), that: | (2.11) |
If
, with at least one of these inequalities being strict, then setting:
, we can rewrite (2.11) as: | (2.12) |
Corollary 2.5 If
, for all
then:
where
is the geometric mean of the numbers
Proof. Since the function
is concave, it follows from the inequality (2.7) that:
If
then we can take
and obtain: | (2.13) |
This inequality holds even when
Application 2.6 Let
, for all
Then we can take
and
We have:
It follows now from (2.13) that:
This is equivalent to:
Corollary 2.7 If
for all
and
then: | (2.14) |
where
is the harmonic mean of the numbers
Proof. The function
is convex. Applying the inequality (2.7) to this function, we get:
If
then by taking
and
in (2.14), we obtain:
Alternative characterizations for means, obtained by different methods, can be found in [6]-[9].Observation 2.8 The means
and
make sense for negative numbers, too. If
, then the inequality (2.14) is reversed, which can be proved very simply by multiplying both sides of this inequality by -1.Application 2.9 Let
, for all
. Then we can take 
, and we have
. It follows now from (2.14) that:
This is equivalent to
The last inequality means:
Corollary 2.10 Let
and
. Then the following inequality holds: | (2.15) |
where:
is the power mean of order
(called also the H¨older mean of order
) of the numbers
In particular if 
and
then: | (2.16) |
Proof. Everything follow by applying the inequality (2.7) to the convex and increasing function
,
.Application 2.11 For all
and all positive numbers
we have:
where
denotes the
mean of
for all
Proof. We simply apply Theorem 2.3 to the numbers
and the function
and
. We have
, which is a convex function since
, and thus the result of our application follows easily.Observation 2.12 All the inequalities from this paper can be reformulated using weighted means, too.
ACKNOWLEDGEMENTS
• The author would like to thank the referees for their kind comments and suggestions that greatly helped him in improving the quality of this paper.• The author would also like to thank Professor Aurel I. Stan, from The Ohio State University, for helping him in preparing this manuscript.
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