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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.
The Null Hypothesis - H0: There is autocorrelation The Alternative Hypothesis - H1: There is no autocorrelation Rejection Criteria: Reject H0 (n-s)R 2 > = (1515 - 4) x (0.
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