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tnich

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Thank you for your reply! Actually I finally understand why using the error matrix is bad. However I am still a bit confused about how Bevington calculates the confidence intervals. He uses a chi squared distribution and for example he uses the fact that for one parameter an increase on 1 for the chi squared is equivalent to a 68% confidence level. However in other online resources (for example: https://lmfit.github.io/lmfit-py/confidence.html) they use an F distribution to define the confidence interval. But the 2 methods don't seem equivalent, as in Bevington the value of number of data points (N in the link I provided) doesn't come in the formula. So which one is the right formula?Data Reduction and Error Analysis for the Physical Sciences, by Bevington and Robinson. It seems to me that equation 3.13 and the discussion around it make clear that covariance terms are important. Also, on page 125 the authors state, "The error matrix can be used to estimate the uncertainty in a calculated result, including the effects of the correlations of the errors." Could you give page numbers and brief quotes of the later contradiction? I am looking at the third edition of the book.

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tnich

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Why is it bad to use the error matrix?

Can you tell me what page of Bevington you are looking at?

Can you tell me what page of Bevington you are looking at?

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