1. Numbers, sets, and induction
2. Proofs and induction; Irrationality of $\sqrt{2}$
3. Least Upper Bounds and Greatest Lower Bounds; Axiom of Completeness, and; Construction of $\mathbb{R}$ from $\mathbb{Q}$
4. Consequences of the Axiom of Completeness; Decimals, Extended Real Number System
5. Dirichlet box principle; Cartesian products, relations and functions
6. Functions and their properties; Trigonometric functions $\sin(\theta)$ and $\cos(\theta)$
7. Axiom of Choice, Cardinality, Cantor's theorem
8. Countable sets, cardinality continuum
9. Inequality between the arithmetic and geometric means; and other useful inequalities
10. The Limit of a Sequence; The Algebraic and Order Limit; Theorems
11. The Squeeze Theorem; The Monotone Convergence Theorem; and other useful theorems
12. Euler's numbers; Subsequences; A First Glance at Infinite Series
13. Toeplitz theorem and applications; Exponential and logarithm function; Bolzano--Weierstrass theorem
14. Completeness; Infinite Series and Euler's numbers
15. Exponential function and logarithm; Upper and Lower limits; Properties of infinite series and; Abel Summation formula
16. Metric spaces basic properties
17. Complete spaces; and Compact sets
18. Compact Sets, Connected Sets; and Cantor set
19. Continuous functions; Continuous functions on compact sets
20. Continuity, compactness and connectivity; Uniform continuity; Sets of Discontinuity
21. Derivatives, the; Mean-Value Theorem and its Consequences; Higher Order Derivatives; Convex and Concave functions
22. Exponential Function and Natural Logarithm Function; Power Series and Taylor's theorem
23. Applications of Calculus: Bernoulli's inequality; and Weighted Mean Inequalities
24. Power series of trigonometric functions done right
25. Riemann Integrals

9. Inequality between the arithmetic and geometric means; and other useful inequalities  PDF

Geometric Mean vs Arithmetic Mean

Geometric and arithmetic means

Let \(a_1,a_2,\ldots,a_n \geq 0\) be given.

Arithmetic mean. We define arithmetic mean of \(a_1,a_2,\ldots,a_n\) by \[A_n=\frac{a_1+a_2+\ldots+a_n}{n}.\]

Geometric mean. We define geometric mean of \(a_1,a_2,\ldots,a_n\) by \[G_n=\sqrt[n]{a_1\cdot a_2 \cdot \ldots \cdot a_n}.\]

Geometric Mean vs Arithmetic Mean

Theorem. For any \(n \in \mathbb{N}\) we have \[G_n \leq A_n.\]

Proof. For \(n=2\) observe that \[(a-b)^2 \geq 0,\]

since \[a^2-2ab+b^2 \geq 0 \ \ \iff \ \ ab \leq \frac{a^2+b^2}{2}.\]

Taking \(a=\sqrt{a_1}\) and \(b=\sqrt{a_2}\) we obtain \[A_2=\frac{a_1+a_2}{2}=\frac{(\sqrt{a_1})^2+(\sqrt{a_2})^2}{2} \geq \sqrt{a_1a_2}=G_2.\]

Cases \(n=4\) and \(n=8\) suggest induction

Case \(n=4\). Note that \[\begin{aligned} &A_4=\frac{a_1+a_2+a_3+a_4}{4}=\frac{1}{2}\left(\frac{a_1+a_2}{2}+\frac{a_3+a_4}{2}\right) \\& \underbrace{\geq}_{{\color{red}A_2 \geq G_2}}\left(\left(a_1a_2\right)^{1/2}\left(a_3a_4\right)^{1/2}\right)^{1 / 2}=(a_1a_2a_3a_4)^{1 / 4}=G_4. \end{aligned}\]


Case \(n=8\). Let us use \(A_4 \geq G_4\) and \(A_2 \geq G_2\) to prove \(A_8 \geq G_8\). \[\begin{aligned} &A_8=\frac{a_1+\ldots+a_8}{8}=\frac{1}{2}\left(\frac{a_1+\ldots+a_4}{4}+\frac{a_5+\ldots+a_8}{4}\right) \\& \underbrace{\geq}_{{\color{red}A_2 \geq G_2}}\left(\frac{a_1+\ldots+a_4}{4}\frac{a_5+\ldots+a_8}{4}\right)^{1 / 2} \\& \underbrace{\geq}_{{\color{red}A_4 \geq G_4}}\left(\left(a_1\ldots a_4\right)^{1 / 4}\left(a_5 \ldots a_8\right)^{1 / 4}\right)^{1 / 2}=\left(a_1\ldots a_8\right)^{1 / 8}=G_8. \end{aligned}\]

Claim and base step

We first use induction to prove \[A_{2^n} \geq G_{2^n}\] for all \(n\in\mathbb N\).

Base step. For \(n=2\) the inequality is true as \[A_2=\frac{a_1+a_2}{2} \geq (a_1a_2)^{1 / 2}=G_2.\]

Inductive step

Let \(P(n)\) be the statement that \(A_{2^n} \geq G_{2^n}\) holds for some \(n\in\mathbb N\).

Inductive step. Now we prove that \({\color{red}P(n) \Longrightarrow P(n+1)}\). Indeed, \[\begin{aligned} A_{2^{n+1}}=&\frac{a_1+\ldots+a_{2^{n+1}}}{2^{n+1}}=\frac{1}{2}\left(\frac{a_1+\ldots+a_{2^n}}{2^n}+\frac{a_{2^n+1}+\ldots+a_{2^{n+1}}}{2^n}\right) \\& \underbrace{\geq}_{{\color{red}A_2 \geq G_2}}\left(\frac{a_1+\ldots+a_{2^n}}{2^n}\frac{a_{2^n+1}+\ldots+a_{2^{n+1}}}{2^n}\right)^{1 / 2} \\& \underbrace{\geq}_{{\color{red}A_{2^n} \geq G_{2^n}}}\left(\left(a_1\ldots a_{2^n}\right)^{1 / 2^{n}}\left(a_{2^n+1} \ldots a_{2^{n+1}}\right)^{1 / 2^n}\right)^{1 / 2}\\ &=\left(a_1\ldots a_{2^{n+1}}\right)^{1 / 2^{n+1}}=G_{2^{n+1}}. \end{aligned}\]

Now we have to show that

\[A_n \geq G_n\]. for all \(n\in\mathbb N\).

We first observe that the following downwards induction holds.

Let \(Q(n)\) be the statement that \[A_n \geq G_n\] holds for some \(n \in \mathbb{N}\). Then \[Q(n-1)\] is also true.

This will follow from the so-called bootstrap phenomenon.

Bootstrap phenomenon

Note that (by \(A_n \geq G_n\) with \(a_1,a_2,\ldots, a_{n-1}, a_n=A_{n-1}\)) one has \[\frac{a_1+\ldots+a_{n-1}+A_{n-1}}{n} \geq \left(a_1 \cdot \ldots \cdot a_{n-1}\cdot A_{n-1}\right)^{1 / n}.\]

But \[\frac{a_1+\ldots+a_{n-1}+A_{n-1}}{n}=\frac{(n-1)A_{n-1}+A_{n-1}}{n}=A_{n-1}.\]

Thus we have shown

Bootstrapping inequality. \[A_{n-1} \geq \left(a_1 \cdot \ldots \cdot a_{n-1}\right)^{1 / n}A_{n-1}^{1 / n}.\]

Hence \[A_{n-1}^{1-1 / n} \geq \left(a_1 \cdot \ldots \cdot a_{n-1}\right)^{1 / n}=G_{n-1}^{(n-1)/n},\] thus \(A_{n-1} \geq G_{n-1}\), which means that \(Q(n-1)\) holds.

Geometric Mean vs Arithmetic Mean: 1/2

Now we can show that

Claim ( \(\star\) ). \[A_n \geq G_n \quad \text{ for all } \quad n \in \mathbb{N}.\]

Proof. We know:

  1. \(A^{2^m} \geq G_{2^m}\) for all \(m \in \mathbb{N}\),

  2. if \(A_k \geq G_k\) holds for some \(k \in \mathbb{N}\), then also holds for \(k-1\), i.e. \(A_{k-1} \geq G_{k-1}\) is true.

Concluding, we can easily prove Claim (\(\star\)). Fix \(n \in \mathbb{N}\) and choose the smallest \(m \in \mathbb{N}\) so that \[2^{m-1}<n \leq 2^{m}.\]

By (1) we know \(A_{2^m} \geq G_{2^m}\) holds.

Geometric Mean vs Arithmetic Mean: 2/2

Claim ( \(\star\) ). \[A_n \geq G_n \quad \text{ for all } \quad n \in \mathbb{N}.\]

By (2) with \(k=2^m\) we deduce \[\begin{aligned} A_{2^m} \geq G_{2^m} \quad \text{ implies } \quad A_{2^m-1} \geq G_{2^m-1}. \end{aligned}\] Repeating \[\begin{aligned} A_{2^m-1} \geq G_{2^m-1} \quad \text{ implies } \quad A_{2^m-2} \geq G_{2^m-2}. \end{aligned}\]

We now apply (2) as many times until we reach \(A_{n} \geq G_{n}\) and the proof is finally completed. $$\tag*{$\blacksquare$}$$

Mean inequalities

Means

Let \(a_1,a_2,\ldots,a_n > 0\) be given. We have the following means.

Arithmetic mean. \[A_n=\frac{a_1+\ldots+a_n}{n};\]

Geometric means. \[G_n=\left(a_1 \cdot \ldots \cdot a_{n}\right)^{1 / n};\]

Harmonic mean. \[H_n=\frac{n}{\frac{1}{a_1}+\frac{1}{a_2}+\ldots+\frac{1}{a_n}};\]

Quadratic mean. \[Q_n=\left(\frac{a_1^2+\ldots+a_n^2}{n}\right)^{1 / 2}.\]

Example. For \(a_1=1\), \(a_2=2\), \(a_3=4\) we have \[A_3=\frac{1+2+4}{3}=\frac{7}{3} \approx 2,333\ldots, \quad G_3=\sqrt[3]{1 \cdot 2 \cdot 4}=2,\] \[H_3=\frac{3}{1+\frac{1}{2}+\frac{1}{4}}=\frac{12}{7}\approx 1,714\ldots, \quad Q_3=\sqrt{7} \approx 2,645\ldots\] \[\min(1,2,4)=1, \qquad \max(1,2,4)=4.\]

Theorem

Theorem. For all \(n \in \mathbb{N}\) and \(a_1,a_2,\ldots,a_n > 0\) we have \[\min(a_1,\ldots,a_n) \leq H_n \leq G_n \leq A_n \leq Q_n \leq \max(a_1,\ldots,a_n).\]

Proof. We will proceed in several steps.

  • We have proved that \(A_n \geq G_n\).

  • To prove \(H_n \leq G_n\) we apply \(A_n \geq G_n\) with \[\frac{1}{a_1},\frac{1}{a_2},\ldots,\frac{1}{a_n}.\] We obtain \[\begin{aligned} G_n^{-1}=\left(\frac{1}{a_1}\cdot \frac{1}{a_2}\cdot \ldots \cdot \frac{1}{a_n}\right)^{1 / n} \leq \frac{\frac{1}{a_1}+\frac{1}{a_2}+\ldots+\frac{1}{a_n}}{n}=H_n^{-1}, \end{aligned}\] thus \(H_n \leq G_n\).

  • To prove inequality \(A_n \leq Q_n\) consider the relation \[\begin{aligned} (a_1+a_2+\ldots+a_n)^2&=a_1^2+a_2^2+\ldots+a_n^2\\ &+2(a_1a_1+a_1a_3+\ldots+a_1a_n)\\ &+2(a_2a_3+a_2a_4+\ldots+a_2a_n)\\ & +\ldots+ 2(a_{n-2}a_{n-1}+a_{n-2}a_n)+2a_{n-1}a_n. \end{aligned}\]

    Since \(2a_ia_j \leq a_i^2+a_j^2\), thus \[\begin{aligned} (a_1+\ldots+a_n)^2 \leq n(a_1^2+\ldots+a_n^2). \end{aligned}\]

    Hence \[\begin{aligned} a_1+\ldots+a_n \leq \left(n(a_1^2+\ldots+a_n^2)\right)^{1/ 2}, \end{aligned}\]

    and consequently \(A_n \leq Q_n\).

  • Finally wlog suppose that \[0<a_1 \leq a_2 \leq \ldots \leq a_n.\]

    then \(a_1=\min(a_1,\ldots,a_n)\), and \(a_n=\max(a_1,\ldots,a_n)\). Hence \[\begin{aligned} H_n=\frac{n}{\frac{1}{a_1}+\frac{1}{a_2}+\ldots+\frac{1}{a_n}} \geq n\frac{a_1}{n}=a_1, \end{aligned}\] and \[\begin{aligned} Q_n=\left(\frac{a_1^2+\ldots+a_n^2}{n}\right)^{1/2} \leq \left(\frac{na_n^2}{n}\right)^{1/2}=a_n. \end{aligned}\] The proof is completed. $$\tag*{$\blacksquare$}$$

AM-GM inequality - example

Example. Prove that for any \(x,y,z>0\) we have \[\frac{x^2}{yz}+\frac{y^2}{xz}+\frac{z^2}{xy} \geq 3.\]

Solution. Consider the numbers \(\frac{x^2}{yz}\), \(\frac{y^2}{xz}\), \(\frac{z^2}{xy}\). Then \[A_3=\frac{\frac{x^2}{yz}+\frac{y^2}{xz}+\frac{z^2}{xy}}{3},\] \[G_3=\sqrt[3]{\frac{x^2}{yz}\cdot\frac{y^2}{xz}\cdot\frac{z^2}{xy}}=1,\] so our inequality is a consequence of \(A_3 \geq G_3\).$$\tag*{$\blacksquare$}$$

Example. If the product of \(n\) positive real numbers is \(1\), then their sum is at least \(n\).

Solution. Let \(a_1,\ldots,a_n>0\) be the numbers such that \[G_n=\sqrt[n]{a_1\cdots a_n}=1,\] so by \(A_n \geq G_n\), \[a_1+\ldots+a_n \geq n G_n=n.\] $$\tag*{$\blacksquare$}$$

Bernoulli inequality

Bernoulli inequality: 1/2

Bernoulli inequality. If \(x>-1\) and \(n \in \mathbb{N}\), then one has \[(1+x)^n \geq 1+nx.\]

Proof. We will use \(A_n \geq G_n\) with \[a_1=a_2=\ldots=a_{n-1}=1 \quad \text{ and }\quad a_n=1+nx.\] Indeed, \[\begin{aligned} A_n=\frac{a_1+\ldots+a_n}{n}=\frac{\overbrace{1+\ldots+1}^{n-1 \text{ times}}+1+nx}{n}=\frac{n(1 +x)}{n}=1+x. \end{aligned}\]

Bernoulli inequality: 2/2

On the other hand \[\begin{aligned} (1+x)=A_n \geq G_n=\left(\overbrace{1 \cdot 1 \cdot \ldots \cdot 1}^{n-1 \text{ times}} \cdot (1+nx)\right)^{1 / n}=(1+nx)^{1 / n}, \end{aligned}\]

which implies \[\begin{aligned} (1+x)^n \geq 1+nx, \end{aligned}\] and we are done. $$\tag*{$\blacksquare$}$$

Bernoulli inequality: generalization

Our aim will be to built tools and generalize Bernoulli’s inequality. We show that the following is true.

Bernoulli inequality - generalization. If \(-1<x \neq 0\) and \(a>1\) or \(a<0\), then \[(1+x)^a>1+ax.\]

If \(-1<x \neq 0\) and \(0 <a<1\), then \[(1+x)^a<1+ax.\]

Cauchy–Schwarz inequality

Cauchy–Schwarz inequality

Cauchy–Schwarz inequality. For any real numbers \(a_1,\ldots,a_n\) and \(b_1,\ldots,b_n\) one has \[\begin{aligned} \left(\sum_{j=1}^na_jb_j\right)^2 \leq \left(\sum_{j=1}^na_j^2\right)\left(\sum_{j=1}^nb_j^2\right). \end{aligned}\]

Proof. Consider the polynomial \[\begin{aligned} &0 \leq (a_1x+b_1)^2+(a_2x+b_2)^2+\ldots+(a_nx+b_n)^2=\\& (a_1^2+\ldots+a_n^2)x^2+2(a_1b_1+a_2b_2+\ldots+a_nb_n)x+(b_1^2+\ldots+b_n^2). \end{aligned}\]

Since the polynomial is nonnegative \[\begin{aligned} \Delta=4(a_1^2+\ldots+a_n^2)(b_1^2+\ldots+b_n^2)-4(a_1b_1+\ldots+a_nb_n) \geq 0 \end{aligned}\] and we are done. $$\tag*{$\blacksquare$}$$

Triangle’s inequality

Triangle’s inequality. For all \(x,y \in \mathbb{R}\) one has \[|x+y| \leq |x|+|y|.\]

Consequently, one has \[\big||x|-|y|\big| \leq |x-y| \leq |x|+|y|.\]

Proof is an easy exercise.

Minkowski’s inequality: 1/3

Minkowski’s inequality. For any real numbers \(a_1,\ldots,a_n\) and \(b_1,\ldots,b_n\) one has \[\left(\sum_{j=1}^n|a_j+b_j|^2\right)^{1 / 2} \leq \left(\sum_{j=1}^n|a_j|^2\right)^{1 / 2}+\left(\sum_{j=1}^n|b_j|^2\right)^{1 / 2}.\]

Proof. Let \[S_n=\left(\sum_{j=1}^{n}|a_j+b_j|^2\right)^{1 / 2}.\]

Minkowski’s inequality: 2/3

Then \[\begin{aligned} S_n^2&=\sum_{j=1}^{n}|a_j+b_j|^2=\sum_{j=1}^{n}|a_j+b_j||a_j+b_j| \\&\leq \sum_{j=1}^{n}|a_j+b_j||a_j|+\sum_{j=1}^{n}|a_j+b_j||b_j|. \end{aligned}\]

By the Cauchy–Schwarz inequality, \[\begin{aligned} S_n^2&\leq \\ \underbrace{\left(\sum_{j=1}^n |a_j+b_j|^2\right)^{1 / 2}}_{=S_n}\left(\sum_{j=1}^n |a_j|^2\right)^{1 / 2} &+\underbrace{\left(\sum_{j=1}^n |a_j+b_j|^2\right)^{1 / 2}}_{=S_n}\left(\sum_{j=1}^n |b_j|^2\right)^{1 / 2} \end{aligned}\]

Minkowski’s inequality: 3/3

\[\begin{aligned} =S_n \left(\left(\sum_{j=1}^n |a_j|^2\right)^{1 / 2}+\left(\sum_{j=1}^n |b_j|^2\right)^{1 / 2}\right). \end{aligned}\]

Thus we have proved a bootstrap inequality, i.e. \[S_n^2 \leq S_n \left(\left(\sum_{j=1}^n |a_j|^2\right)^{1 / 2}+\left(\sum_{j=1}^n |b_j|^2\right)^{1 / 2}\right).\]

Hence \[S_n \leq \left(\sum_{j=1}^n |a_j|^2\right)^{1 / 2}+\left(\sum_{j=1}^n |b_j|^2\right)^{1 / 2}.\] $$\tag*{$\blacksquare$}$$

Hölder’s inequality

Hölder’s inequality. Let \(1<p,q<\infty\) be such that \(\frac{1}{p}+\frac{1}{q}=1\). Then for any real numbers \(a_1,\ldots,a_n\) and \(b_1,\ldots,b_n\) one has \[\begin{aligned} \sum_{j=1}^n|a_jb_j| \leq \left(\sum_{j=1}^n|a_j|^p\right)^{1 / p}\left(\sum_{j=1}^n|b_j|^q\right)^{1 / q}. \end{aligned}\]

This inequality is an extension of the Cauchy–Schwarz inequality. However at the moment we do not have tools to prove this inequality.

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