Find the coordinates and the nature of any turning points (maximum and minimum)

In summary, you found the turning points for y'=-1, y\left(\frac{9-\sqrt{17}}{16}\right), and y\left(\frac{9+\sqrt{17}}{16}\right) using the first or second derivative tests, and determined that these points correspond to x=\frac{9\pm\sqrt{17}}{16} and x=0, respectively.
  • #1
b4rn5ey
3
0
So I've been trying to wrap my head around this one for several hours now and it just has me stumped. I'm begging, someone, anyone, walk me through it before I swear off numbers for life hahah (Part b)

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Thanks in advance for any help anyone can provide :)
 

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  • #2
Hello, and welcome to MHB, b4rn5ey! (Wave)

In part (a) of the problem, you correctly found:

\(\displaystyle y'=16x^3-18x^2+4x\)

To find the turning points, and we observe that $y'=0$ at such points, we need to find the roots of $y'$ (our critical values)...that is, we need to solve:

\(\displaystyle 16x^3-18x^2+4x=0\)

I would suggest factoring to get a linear factor and a quadratic factor...what do you get?
 
  • #3
MarkFL said:
Hello, and welcome to MHB, b4rn5ey! (Wave)

In part (a) of the problem, you correctly found:

\(\displaystyle y'=16x^3-18x^2+4x\)

To find the turning points, and we observe that $y'=0$ at such points, we need to find the roots of $y'$ (our critical values)...that is, we need to solve:

\(\displaystyle 16x^3-18x^2+4x=0\)

I would suggest factoring to get a linear factor and a quadratic factor...what do you get?
Thanks for the reply..

So I've tried to find the first turning point using your advice..

This seem right? Or am i walking off track>

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  • #4
I agree with your factorization:

\(\displaystyle y'=2x\left(8x^2-9x+2\right)=0\)

I also agree with the critical values you obtained from the quadratic factor:

\(\displaystyle x=\frac{9\pm\sqrt{17}}{16}\)

However, there is another factor involving $x$ that must be equated to zero, which is simply:

\(\displaystyle x=0\)

So, this gives us 3 critical values, and 3 possible turning points:

\(\displaystyle y(0)=-1\)

\(\displaystyle y\left(\frac{9-\sqrt{17}}{16}\right)=\frac{51\sqrt{17}-2155}{2048}\)

\(\displaystyle y\left(\frac{9+\sqrt{17}}{16}\right)=-\frac{51\sqrt{17}+2155}{2048}\)

Now, you need to determine the nature of these points, using either the first or second derivative tests. :D

If you are going to upload images of your work rather than typeset it for easier reading, please attach the images inline rather than hot-linking to the image...this way I won't have to follow the link, download the image, resize and crop the image, and edit your post to attach it inline so it can be read in the post.
 

Related to Find the coordinates and the nature of any turning points (maximum and minimum)

1. What are turning points in a graph?

Turning points are points on a graph where the direction of the curve changes, from increasing to decreasing or vice versa. They are also known as extrema or critical points.

2. How do you find the coordinates of a turning point?

To find the coordinates of a turning point, you need to take the derivative of the function and set it equal to zero. Then, solve for the independent variable to get the x-coordinate. Plug this value back into the original function to get the y-coordinate.

3. What is the nature of a turning point?

The nature of a turning point can be classified as either a maximum or a minimum. A maximum turning point is the highest point on a curve, while a minimum turning point is the lowest point on a curve.

4. How do you determine if a turning point is a maximum or a minimum?

To determine the nature of a turning point, you can use the second derivative test. If the second derivative is positive at the turning point, then it is a minimum. If the second derivative is negative, then it is a maximum. If the second derivative is zero, then the test is inconclusive and you will need to use other methods to determine the nature of the turning point.

5. Why is it important to find the coordinates and nature of turning points?

Finding the coordinates and nature of turning points can provide valuable information about a function, such as the location of maximum and minimum values. This can be useful in optimization problems, where the goal is to find the maximum or minimum value of a function. It can also help in understanding the behavior and characteristics of a function.

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