Sum of squares of average change is less than

In summary, the problem asks to show that for any two differentiable functions defined on a closed interval, there exists a point on the interval where the sum of squares of their average change is less than or equal to the sum of squares of their derivatives at that point. This can be proven using the properties of continuous functions and integrals.
  • #1
caffeinemachine
Gold Member
MHB
816
15
Hello MHB,

I have no good ideas on how to go about solving the following:

Let $f:[a,b]\to\mathbb R$ and $g:[a,b]\to\mathbb R$ be real values functions both of which are differentiable in $(a,b)$. Show that there is an $x\in(a,b)$ such that $$\left(\frac{f(b)-f(a)}{b-a}\right)^2+\left(\frac{g(b)-g(a)}{b-a}\right)^2\leq (f'(x))^2+(g'(x))^2$$

Please help.
 
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  • #2
Re: Sum of squares of average change is less than ...

caffeinemachine said:
Hello MHB,

I have no good ideas on how to go about solving the following:

Let $f:[a,b]\to\mathbb R$ and $g:[a,b]\to\mathbb R$ be real values functions both of which are differentiable in $(a,b)$. Show that there is an $x\in(a,b)$ such that $$\left(\frac{f(b)-f(a)}{b-a}\right)^2+\left(\frac{g(b)-g(a)}{b-a}\right)^2\leq (f'(x))^2+(g'(x))^2$$

Please help.
Here's an idea to get you started. Define a path in 2-dimensional space by the function $h:[a,b] \to \mathbb{R}^2$ given by $h(t) = \bigl(f(t),g(t)\bigr)\ (a\leqslant t\leqslant b).$ Then the distance between the endpoints is less than (or equal to) the length of the path.
 
  • #3
Re: Sum of squares of average change is less than ...

Opalg said:
Here's an idea to get you started. Define a path in 2-dimensional space by the function $h:[a,b] \to \mathbb{R}^2$ given by $h(t) = \bigl(f(t),g(t)\bigr)\ (a\leqslant t\leqslant b).$ Then the distance between the endpoints is less than (or equal to) the length of the path.
Opalg said:
Here's an idea to get you started. Define a path in 2-dimensional space by the function $h:[a,b] \to \mathbb{R}^2$ given by $h(t) = \bigl(f(t),g(t)\bigr)\ (a\leqslant t\leqslant b).$ Then the distance between the endpoints is less than (or equal to) the length of the path.
So the above says that:

$\sqrt{(f(b)-f(a))^2+(g(b)-g(a))^2}\leq \displaystyle\int_a^b\left[\sqrt{(f'(x))^2+(g'(x))^2}\right]dx$. Now we use the fact that if $h:[a,b]\to\mathbb R$ is a continuous function then $\int_a^bh(x)dx\leq h(x_0)(b-a)$ for some $x_0\in (a,b)$.

Is this correct?
 
  • #4
Re: Sum of squares of average change is less than ...

caffeinemachine said:
So the above says that:

$\sqrt{(f(b)-f(a))^2+(g(b)-g(a))^2}\leq \displaystyle\int_a^b\left[\sqrt{(f'(x))^2+(g'(x))^2}\right]dx$. Now we use the fact that if $h:[a,b]\to\mathbb R$ is a continuous function then $\int_a^bh(x)dx\leq h(x_0)(b-a)$ for some $x_0\in (a,b)$.

Is this correct?
That's exactly what I was thinking of. (Nod)
 
  • #5


I would approach this problem by first breaking it down into smaller, more manageable parts. I would start by looking at the left side of the inequality and trying to understand what it represents. The sum of squares of average change can be interpreted as the average rate of change of both functions over the interval [a,b], squared and added together. This can also be thought of as the total change in both functions over the interval, squared and added together.

Next, I would look at the right side of the inequality and try to understand what it represents. The right side is the sum of squares of the derivatives of both functions evaluated at some point x in the interval (a,b). This can be interpreted as the instantaneous rate of change of both functions at a specific point x.

Based on this interpretation, it makes intuitive sense that the total change over an interval would be less than or equal to the instantaneous change at a specific point. This is because the instantaneous change at a point is the limit of the average change over smaller and smaller intervals. Therefore, it is reasonable to expect that there would be at least one point x in the interval (a,b) where the instantaneous change is larger than or equal to the average change over the entire interval.

To prove this mathematically, I would use the Mean Value Theorem, which states that for a differentiable function over an interval, there exists at least one point where the derivative is equal to the average rate of change over that interval. This point can be used to show that the right side of the inequality is greater than or equal to the left side, thus proving the statement.

In conclusion, as a scientist, I would approach this problem by first understanding the concepts behind the inequality and then using mathematical tools such as the Mean Value Theorem to prove it. This approach allows for a deeper understanding of the problem and its solution, rather than simply relying on a formula or algorithm.
 

Related to Sum of squares of average change is less than

What does "Sum of squares of average change is less than" mean?

The sum of squares of average change refers to the sum of the squares of the differences between each data point and the average of all the data points. When this sum is less than a given value, it indicates that the data points are closely clustered around the average and there is not a significant amount of variability in the data.

Why is the "Sum of squares of average change is less than" important?

This measure is important in statistics because it allows us to quantify the amount of variability in a data set. A small sum of squares of average change indicates that the data is consistent and reliable, while a large sum indicates that there is a lot of variability and the data may not be as trustworthy.

How is the "Sum of squares of average change is less than" calculated?

To calculate the sum of squares of average change, you first find the average of all the data points. Then, for each data point, you calculate the difference between that data point and the average, and square that difference. Finally, you add up all of these squared differences to get the sum of squares of average change.

What does it mean if the "Sum of squares of average change is less than" is zero?

If the sum of squares of average change is equal to zero, it means that all of the data points are exactly equal to the average. This indicates that there is no variability in the data and all of the data points are consistent and reliable.

How is the "Sum of squares of average change is less than" used in statistical analysis?

The sum of squares of average change is often used as a measure of variability in a data set. It can be used to compare the variability between different data sets or to track changes in variability over time. It is also used in various statistical tests and models to analyze the relationship between variables and to make predictions.

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