What is a lack of fit sum of squares analysis?

1 Answer
SCooke
Feb 19, 2018

Basically, just the inverse of the correlation coefficient.

Explanation:

Normally, we are interested in how well the points fit a modeled line. In a sum of the squares analysis that is the correlation or regression coefficient.

If you want to see how poorly the data fit a model, you could take the inverse. Then, a "high" number (anything over 1.2 for example) indicates a POOR fit.

Personally, I don't see any value in the practice.

For example if R=0.3547, which would be a poor correlation, the inverse is 1R=2.82

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