Finding the Gradient and Solving for Zero Points on a Cubic Curve

In summary: This means that the curve never crosses the x-axis and therefore never has a point where the gradient is zero.In summary, we are asked to find the gradient of the curve y = 2x3 - 5x2 + 46x + 87 at the point where it crosses the x-axis. We find the derivative of the function to be dy/dx = 6x2 - 10x + 46 and set it equal to zero to find the points where the gradient is zero. However, we are then asked to show that there are no points on the curve where the gradient is zero by proving that the equation has no real solutions. By solving the equation, we find that the roots are complex numbers, meaning there
  • #1
maobadi
22
0

Homework Statement



1. Calculate the gradient of the curve y = 2x3 - 5x2 + 46x + 87 at the point where it crosses the x-axix.

2. Show by differentiation and solving a quadratic equation, that there are no points on the above curve where the gradient is zero.

Homework Equations



y = 2x3 - 5x2 + 46x + 87

The Attempt at a Solution



dy/dx = 6x2 - 10x + 46

It crossess at x-axis where y = 0 ( it it right...?) I then calculate the roots of the equation, and the two roots of x are the points where it crossess the x-axis.

How do I do the part 2 problem...?
 
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  • #2
You have found the derivative of the function, so how about setting it equal to zero. If you then solve it, you will find all the x values where the derivative is zero (if they exist). What should you expect if no zero derivatives exist?
 
  • #3
what do you mean by "What should you expect if no zero derivatives exist?" What do I do?
My question for the problem is are both part1 and part 2 the same thing. I mean part 1 says calculate and part 2 says show by differentiation and solving a quadratic equation. Do I have to differentiate(for part 2) one more time..?
 
  • #4
The question asks you to show that the gradient of y = 2x3 - 5x2 + 46x + 87 is never zero. You have already found the derivative of the function, dy/dx = 6x2 - 10x + 46, which is the first step.

You have been asked to show that there exists no x such that the gradient is zero i.e. there are no such x values that make dy/dx = 0, or 6x2 - 10x + 46 = 0. So your task then becomes to show that no real x values satisfy the equation 6x2 - 10x + 46 = 0 i.e. the equation has no solutions. How can you show it has no real solutions?
 
  • #5
solving the quadratic equation i get x = (5+18.5i) and (5-18.5i) which are the complex roots and does this mean that it will never touch the x-axis...?
 
  • #6
maobadi said:
solving the quadratic equation i get x = (5+18.5i) and (5-18.5i) which are the complex roots and does this mean that it will never touch the x-axis...?

Right. By showing that the equation has only non-real solutions, you have shown that there exists no real value of x that makes dy/dx equal zero i.e. the curve never has a zero gradient.
 

Related to Finding the Gradient and Solving for Zero Points on a Cubic Curve

1. What is the difference between gradient and differentiation?

The gradient is a vector that represents the direction and magnitude of the steepest increase of a function at a given point. Differentiation, on the other hand, is a mathematical tool used to find the rate of change of a function at a specific point.

2. How is the gradient calculated?

The gradient is calculated by taking the partial derivative of a function with respect to each of its variables and combining them into a vector. This vector represents the direction in which the function increases the most rapidly at a given point.

3. What is the relationship between gradient and slope?

The gradient and slope are closely related concepts. The slope of a line represents the rate of change of the dependent variable with respect to the independent variable. Similarly, the gradient of a function represents the rate of change of the function with respect to each of its variables.

4. Why is the gradient important in machine learning?

In machine learning, the gradient is an essential tool for optimization algorithms. It is used to update the parameters of a model in the direction that minimizes the error between the predicted and actual values. This process is known as gradient descent.

5. Can the gradient be negative?

Yes, the gradient can be negative. A negative gradient indicates that the function is decreasing in the direction of the gradient. In other words, the function is decreasing at a faster rate in that direction than in any other direction.

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