MHB Inequality Challenge: Prove $x^x \ge (x+1/2)^{x+1}$ for $x>0$

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The inequality \( x^x \ge \left( \frac{x+1}{2} \right)^{x+1} \) for \( x > 0 \) can be proven by analyzing the function \( f(x) = x^x - \left( \frac{x+1}{2} \right)^{x+1} \). Taking the logarithm and differentiating leads to the conclusion that \( \ln f(x) \) has a minimum at \( x = 1 \), where \( f(1) = 0 \), thus confirming \( f(x) \geq 0 \) for all \( x > 0 \). An alternative proof using Jensen's Inequality demonstrates that the convexity of \( f(x) = x \ln x \) supports the original inequality. Both methods validate that \( x^x \) is indeed greater than or equal to \( \left( \frac{x+1}{2} \right)^{x+1} \) for positive \( x \).
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Prove $$x^x \ge \left( \frac{x+1}{2} \right)^{x+1}$$ for $x>0$.
 
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anemone said:
Prove $$x^x \ge \left( \frac{x+1}{2} \right)^{x+1}$$ for $x>0$.
[sp]We want to show that $f(x) = x^x - \bigl( \frac{x+1}{2} \bigr)^{x+1} \geqslant0$ for all $x>0$. Take logs, then differentiate: $$\ln f(x) = x\ln x - (x+1)\ln\bigl( \tfrac{x+1}{2} \bigr),$$ $$\tfrac d{dx}(\ln f(x)) = \ln x + 1 - \ln\bigl( \tfrac{x+1}{2} \bigr) - 1 = \ln\bigl( \tfrac{2x}{x+1} \bigr).$$ But $\ln\bigl( \frac{2x}{x+1} \bigr)$ is zero when $x=1$, negative when $x<1$ and positive when $x>1$. Thus $\ln(f(x))$ has a minimum value when $x=1$, hence so does $f(x)$. But $f(1) = 0$. Therefore $f(x)\geqslant0$ for all $x>0$, as required.[/sp]
Edit. Oops! Anemone kindly points out a grotesque blunder in the way I presented that argument. Here is what I should have said.
[sp]Notice that $x^x \geqslant \bigl( \frac{x+1}{2} \bigr)^{x+1}$ is equivalent to $\dfrac{x^x}{\bigl( \frac{x+1}{2} \bigr)^{x+1}} \geqslant 1$. Take logs to see that this in turn is equivalent to $x\ln x - (x+1)\ln\bigl( \tfrac{x+1}{2} \bigr) \geqslant0$. That can be proved as in my attempt above.[/sp]
 
Last edited:
Opalg said:
[sp]We want to show that $f(x) = x^x - \bigl( \frac{x+1}{2} \bigr)^{x+1} \geqslant0$ for all $x>0$. Take logs, then differentiate: $$\ln f(x) = x\ln x - (x+1)\ln\bigl( \tfrac{x+1}{2} \bigr),$$ $$\tfrac d{dx}(\ln f(x)) = \ln x + 1 - \ln\bigl( \tfrac{x+1}{2} \bigr) - 1 = \ln\bigl( \tfrac{2x}{x+1} \bigr).$$ But $\ln\bigl( \frac{2x}{x+1} \bigr)$ is zero when $x=1$, negative when $x<1$ and positive when $x>1$. Thus $\ln(f(x))$ has a minimum value when $x=1$, hence so does $f(x)$. But $f(1) = 0$. Therefore $f(x)\geqslant0$ for all $x>0$, as required.[/sp]
Edit. Oops! Anemone kindly points out a grotesque blunder in the way I presented that argument. Here is what I should have said.
[sp]Notice that $x^x \geqslant \bigl( \frac{x+1}{2} \bigr)^{x+1}$ is equivalent to $\dfrac{x^x}{\bigl( \frac{x+1}{2} \bigr)^{x+1}} \geqslant 1$. Take logs to see that this in turn is equivalent to $x\ln x - (x+1)\ln\bigl( \tfrac{x+1}{2} \bigr) \geqslant0$. That can be proved as in my attempt above.[/sp]

Hi Opalg,

Thanks for participating and I want to show you and those who read this thread another method (a method proposed by other) to prove this inequality using the Jensen Inequality...

Let $$f(x)=x \ln x$$

Differentiate the function of f of x twice we got $$f''(x)=\frac{1}{x} (>0) $$ for all $x$.

This means $f(x)$ is a convex function in the domain $x>0$ and Jensen inequality tells us if a function is convex, we have

$$f\left( \frac{\sum x_i}{n}\right) \le \frac{\sum f(x_i)}{n}$$

$$f\left( \frac{x+1}{2}\right) \le \frac{f(x)+f(1)}{2}$$

$$\left( \frac{x+1}{2}\right) \ln \left( \frac{x+1}{2}\right) \le \frac{x\ln x+1 \ln 1}{2}$$

$$\left( \frac{x+1}{2}\right) \ln \left( \frac{x+1}{2}\right) \le \frac{x\ln x}{2}$$

$$\cancel{2}\left( \frac{x+1}{\cancel{2}}\right) \ln \left( \frac{x+1}{2}\right) \le x\ln x$$

$$ \ln \left( \frac{x+1}{2}\right)^{x+1} \le \ln x^x$$

$$\therefore x^x \ge \left( \frac{x+1}{2}\right)^{x+1}$$
 
I have been insisting to my statistics students that for probabilities, the rule is the number of significant figures is the number of digits past the leading zeros or leading nines. For example to give 4 significant figures for a probability: 0.000001234 and 0.99999991234 are the correct number of decimal places. That way the complementary probability can also be given to the same significant figures ( 0.999998766 and 0.00000008766 respectively). More generally if you have a value that...

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