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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 biggest and smallest variate values among the sample of observations. Significant in various regions, for instance flood levels of the river, speed of wind and snowfall.
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I need a statistics project done. How much will it cost?
The regression analysis is used to fit a model describing the relationship of a dependent variable with independent variable(s). Here we have fitted three regression models:
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