Error on slope using LSQ method

In summary, the LSQ method is used to find the error on the slope of a set of data points. The formula for the error on the slope is σm = σy√(n/Δ), where σy = √(1/n-2(Σ(yk - y(xk))^2)) and Δ = nΣxk^2 - (Σxk)^2. However, there may be errors in the equation or calculations, as Δ cannot be a negative number. Clarification is needed on the meaning of y(xk) in the equation.
  • #1
Matt21
14
0

Homework Statement


Three points are given with errors on y coordinates.
(2.00,4.70±0.36); (4.00,6.8&±0.45); (5.00, 9.10±0.50)
Using LSQ method, find the error on slope.

Homework Equations


σm = σy√(n/Δ), where σy = √(1/n-2(Σ(yk - y(xk))^2)) and Δ = nΣxk^2 - (Σxk)^2

The Attempt at a Solution


I do not know if this is the correct equation or if I made an error in my calculations but what I got was:
σy = 1/3-2((4.7-4.7(2))^2+(6.8-6.8(4))^2+(9.1-9.1(5))^2) = 42 and
Δ = (2^2+4^2+5^2)-(2+4+5)^2 = -76
n = 3
Obviously I can't use Δ since you can't get a root of a negative number. Can anyone see what I'm doing wrong? Any help would be much appreciated.
 
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  • #2
Matt21 said:
1/n-2(Σ(yk - y(xk))^2))
That's a very strange looking expression. Are you sure about the minus sign after 1/n?
 
  • #3
Yes I'm positive. The formula given in my notes was √((1/n-2)(Σ(yk - y(xk))^2)
 
  • #4
Matt21 said:
Yes I'm positive. The formula given in my notes was √((1/n-2)(Σ(yk - y(xk))^2)
Ah, you mean √(1/(n-2)(Σ(yk - y(xk))^2)), i.e. ##\sqrt{\frac 1{n-2}\Sigma( y_k-y(x_k))^2}##? That would make more sense. Originally you had √((1/n)-2Σ(yk - y(xk))^2)), i.e. ##\sqrt{\frac 1n-2\Sigma(y_k-y(x_k))^2}##.
By the way, please clarify what you mean by y(xk).
 
  • #5
Yes that was the equation was trying to convey. In regards to y(xk) I would assume that means y*(xk) where xk = x1, x2, x3...xk
 
Last edited:
  • #6
Δ = (3*(2^2+4^2+5^2))-(2+4+5)^2 = 14
 

Related to Error on slope using LSQ method

What is the LSQ method?

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

What is slope error in the LSQ method?

Slope error in the LSQ method is the measure of how much the slope of the best fit line deviates from the true slope of the data. It is calculated by finding the difference between the estimated slope and the actual slope.

How is slope error calculated in the LSQ method?

Slope error in the LSQ method is calculated using the formula: error = (standard deviation of y values / standard deviation of x values) * (correlation coefficient * standard deviation of x values).

What factors can contribute to slope error in the LSQ method?

Some factors that can contribute to slope error in the LSQ method include outliers in the data, measurement errors, and incorrect assumptions about the underlying relationship between the variables.

How can slope error be minimized in the LSQ method?

To minimize slope error in the LSQ method, it is important to have a large and representative sample size, remove any outliers or errors in the data, and ensure that the assumptions about the data are valid. Additionally, using a different method such as a weighted LSQ method may also help to reduce slope error.

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