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R-squared is regarded as the coefficient of determination and is used to give the proportion of the fluctuation of the variance of one variable to another variable. R-squared also establishes the percentage of data that is near to goodness of fit.
S = 0.0903972 R-Sq = 26.3% R-Sq(adj) = 26.1%
In this case R-squared is 26.3%; this indicates that there is a variation in Y (Wfood) in relation to the linear relationship between the Y and X variables. The remaining percentage (73.7%) is the variation which is unknown.
The adjusted R-squared figure of 26.1% is a more accurate measure of the goodness of fit and as it is lower than r-squared and it indicates that certain explanatory variables are missing therefore the fluctuation of the dependent variable is not fully measured.
Longitudinal data : The data arising when each of the number of subjects or patients give rise to the vector of measurements representing same variable observed at the number of di
elements , importance, limitation, and theories
literature review of latin square design.
i have an assignment for experimental design which is must done by SAS program can you help me also i need to hand in the assignment till thursday shall i send it for you ?
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