How to find the f(x) (least square method)

In summary, the person is seeking help in finding the f(x) value to complete a chart. They are looking for a memory jog and not for someone to do the work for them. They have provided some data points but need help in finding the f(x) value. They also mentioned that it has been many years since they attempted this problem.
  • #1
mjmara
2
0
Hi my first post , I hope I chose the right forum?

I'm here looking for a memory jog not for someone to do my work, I'm trying to remember how to find the f(x) to complete this chart , there is many more data points but I'm just providing you with the top line , I shall do the rest myself, can someone help me please?
It's been many years since I attempted this problem :(


x y x^2 xy f(x) f(x)-y (f(x)-y)^2
________________________________________________
-8 6.8 64 -54.4 ?
 
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  • #2
sorry

the format is all messed up

here

x___y___x^2___x.y____f(x)
-8__6.8__64____-54.4__?sorry for the format but this is the best I can do

x= -8
y= 6.8
x^2 = 64
x.y = -54.4
f(x) = ?
 
  • #3
It still is not at all clear what you are asking. Yes, if x= -8 and y= 6.8, then [itex]x^2= 64[/itex] and [itex]xy= -54.4[/itex] but that has nothing to do with some function, "f". Do you have any other information?
 
  • #4
mjmara said:
I'm here looking for a memory jog not for someone to do my work, I'm trying to remember how to find the f(x) to complete this chart
A google search on method of least squares will find some good examples for you to follow, if I have you right. Here is one that may help.
 

FAQ: How to find the f(x) (least square method)

What is the least square method?

The least square method is a mathematical technique used to find the line of best fit for a set of data points. It minimizes the sum of the squared distances between the actual data points and the predicted values from the line.

How is the least square method used to find the f(x)?

The least square method can be used to find the f(x) by first plotting the data points on a graph and then fitting a line to those points using the method. The f(x) can then be determined by using the equation of the line.

What is the purpose of finding the f(x) using the least square method?

The purpose of finding the f(x) using the least square method is to create a line of best fit that can be used to predict the value of y for any given value of x. This can be useful in analyzing and making predictions based on data.

What are the limitations of the least square method?

The least square method assumes that the relationship between the variables is linear, which may not always be the case. It also assumes that all data points have equal importance, which may not be true in some cases. Additionally, outliers can significantly affect the accuracy of the line of best fit.

Can the least square method be used for non-linear data?

No, the least square method is only applicable for linear data. For non-linear data, other methods such as polynomial regression or exponential regression may be more appropriate.

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