I have an enormous dataset and for each row, I have a predicted value, and in the same row, there are a few characteristics(independent variables). I have set an ideal linear regression for this dataset. Now, I want to compare the set of independent variables of my ideal regression with the regression of each every row of my dataset. I appreciate for any help....thank you!
The coefficient of determination or the ratio of variances is the common criterion.
Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures (such as the "variation" among and between groups) used to analyze the differences among means in a sample.
I suggest SPSS program
Geoscientists examples of ANOVA
Conference Paper Application of the Analysis of Variance for Converting Dynam...
Article Investigation of static and dynamic bulk moduli in a carbonate field
None the X's are fixed not variable. Read a linear models book. I like kutner etal Applied Linear Statistical models
The correct way of comparison is the difference between AIC ((step down or step up).
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