Finding the equation to a non-linear set of points

In summary, the problem asks for the equation of a set of four points. The points do not form a linear pattern, so finding the slope and intercept will not work. The suggestion is to use linear regression analysis or a piecewise function of two or three lines. Another option is to use a unique cubic polynomial that passes through the four points, using the points to solve for the coefficients.
  • #1
Joshk80k
17
0

Homework Statement



Determine the equation of the following points:

(12. 270)
(14, 300)
(16, 330)
(18. 380)

Homework Equations



The Attempt at a Solution



I realized right away that this is not a linear set of points, so it wouldn't work out to just find the slope between two points and to find the intercept. I know the answer won't be in the format y = mx+b, but I'm not really sure how to solve this.

I guess what's bothering me is the fact that the equation jumps 20 after a seemingly normal pattern. Any tips as to what direction I should take this problem next?
 
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  • #2
Do you know how to do linear regression analysis? Because that sounds like what you want to do.
 
  • #3
No, I don't know how to do that - I'll look it up though, thanks =)
 
  • #4
This is either a linear fit or a piecewise function of two lines.
 
  • #5
A "linear regression" line or "least squares line" is a line that does NOT go through all the points but comes "closest" in the sense of the average distance from each point to the line being smallest.

You could, as zachach suggests, use a piecewise linear function- although you might need 3, not two pieces- a line from (12. 270) to (14, 300), a line from (14, 300) to (16, 330), and a line from (16, 330) to (18. 380).

It is also true that there exists a unique n-1 or less degree polynomial through any given n points. Here you have four points so there exist a unique cubic (or less) polynomial whose graph passes through those four points.

Write the polynomial as \(\displaystyle y= ax^3+ bx+ c+ d\) and put in the given x and y values to get four linear equations to solve for a, b, c, and d.
 

1. How do I find the equation for a non-linear set of points?

To find the equation for a non-linear set of points, you can use different methods such as graphing, interpolation, or regression. These methods involve plotting the points on a graph and then using mathematical techniques to determine the best-fit equation that describes the relationship between the variables.

2. What is interpolation and how does it help in finding the equation?

Interpolation is a method used to estimate values between known data points. In the context of finding the equation for a non-linear set of points, interpolation can help by providing additional data points that can be used to determine the shape and trend of the curve. This can make it easier to find the best-fit equation for the given set of points.

3. Can I use regression to find the equation for any type of non-linear data?

Regression is a statistical method used to identify and analyze the relationship between variables. It can be used to find the equation for a wide range of non-linear data, but it may not always be the most accurate method. It is important to consider the nature of the data and choose the appropriate regression model for the best results.

4. What is the difference between linear and non-linear equations?

A linear equation is a mathematical expression that can be written in the form y = mx + b, where m and b are constants and x is the variable. This means that the relationship between the variables is a straight line. On the other hand, a non-linear equation does not follow this form and can have a curved or non-linear relationship between the variables.

5. Are there any software or tools that can help in finding the equation for a non-linear set of points?

Yes, there are many software and tools available that can assist in finding the equation for a non-linear set of points. Some popular options include Microsoft Excel, MATLAB, and Python. These programs have built-in functions or libraries that can perform regression analysis and find the best-fit equation for a given set of points.

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