Undergrad Proving that convexity implies second order derivative being positive

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The discussion focuses on proving that convexity implies a positive second derivative. The user attempts to establish this by using the definition of convexity and the intermediate value theorem to show that the derivative at one point is less than the derivative at another point. They realize that they need to prove the inequality holds for all points, not just one. A key question arises about the method of taking limits, specifically whether to let λ approach zero or to let the difference between points shrink. The conversation highlights the need for a clearer understanding of how to demonstrate that the first derivative is increasing for all points in the interval.
hmparticle9
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There are probably loads of proofs of this online, but I do not want to cheat. Here is my attempt:

Convexity says that
$$f(\lambda a + (1-\lambda)b) \leq \lambda f(a) + (1-\lambda) f(b)$$
$$f(b + \lambda(a-b)) \leq f(b) + \lambda (f(a) - f(b))$$

We know from the intermediate value theorem that there exists a ##c \in (b,a)## such that
$$\frac{f(a) - f(b)}{a-b} = f'(c).$$

Hence
$$f(b + \lambda(a-b)) \leq f(b) + \lambda (a - b) f'(c))$$
$$\frac{f(b + \lambda(a-b)) - f(b)}{\lambda(a-b)} \leq f'(c))$$
taking the limit ##\lambda \rightarrow 0##
$$f'(b) \leq f'(c)$$

This is not enough. I need to show that the above holds for all ##c##. I have shown that there exists one such c. Could I have some hints please? What I am getting at is that a function ##f## such that ##f''(x)>0## for all ##x## has the property that ##f'(x) > f'(y)## if ##x>y##
 
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hmparticle9 said:
taking the limit ##\lambda \rightarrow 0##
Why do you take the limit ##\lambda \rightarrow 0##, instead of letting the difference ##h \equiv b-a## go to zero?
 
What difference would that make?
 
I just realized that my proof is even more wrong. I need to show that ##f'(x) > f'(y)## for ##x > y##. Sorry guys. I am well off.
 
I think I understand where you are coming from now. If we let ##a## tend to ##b## then since ##c## is in ##(b,a)## we must have ##f'(b) < f'(c)##. But is that enough?
 
We can say
$$f'(b) < f'(b+\epsilon) < f'(b+2\epsilon) < ... < f'(c)$$
for some ##b < c##.
 
hmparticle9 said:
There are probably loads of proofs of this online, but I do not want to cheat. Here is my attempt:

Convexity says that
$$f(\lambda a + (1-\lambda)b) \leq \lambda f(a) + (1-\lambda) f(b)$$
$$f(b + \lambda(a-b)) \leq f(b) + \lambda (f(a) - f(b))$$

It's a bit confusing to take ##b < a##; usually we have ##a < b##.

My approach would be to define $$
g : [0,1]\to\mathbb{R} : x \mapsto f(b) + x(f(a) - f(b)) - f(b+ x(a - b)) \geq 0.$$ Now ##g(0) = g(1) = 0## and the constraint on the sign of ##g## allows you to say something about the signs of ##g'(0)## and ##g'(1)##, and hence about ##f'(b)## and ##f'(a)##.
 

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