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is "close" to the observed y-value, Yi' for i = 1,2, ... ,27. How exactly do we measure the collective closeness of the fitted y-values to the observed y-values The various regression methods presented in the following chapters correspond to different ways of measuring closeness. Suppose we have chosen a regression method and have obtained estimates ~()' ~I' ~2' and ~y The equation Y = ~() + ~I XI + ~2X2 + ~JX3 is called the estimated regression equation or the fitted regression equation. This equation has several uses. First, it serves as a concise description of a major pattern in the observed data. It describes an approximate relationship between vitamin B2 and the other three variables. The values Yi tend to be close to ~o + ~IXtl + ~2Xi2 + ~JXiJ. Second, it could be used to predict the concentration of vitamin B2 in future harvests of turnip greens with possibly different degrees of sunlight, soil moisture, and air temperature. If in the future we measure the values XI' X 2, and X 3, we could predict that the value of Y will be near Y. Third, the fitted regression equation provides a basis for testing the significance of the relationship between the response variable and the explanatory variables. code 128 barcode in excel Create Barcodes With (Or Without) Excel VBA
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Directly insert Code 128 bar code in Excel without any barcode fonts. Download Trial Package for Free | User Guide included. An observed value YI of the response variable differs from the average by the deviation Yi - y. The deviation can be split into two parts: Yi - Y = (Yi - y) + (9i - y). The second part is the part of the deviation that is explained by the relationship Yi = ffio + ffi.Xil + ... +ffipx iP of the response variable with the explanatory variables. The sum L:(Yi - y)2 can be regarded as the total variability observed in the response variable, and the sum L:(Yi - y)2 can be regarded as the amount of this variability that is explained. Thus R2 is the proportion of the total variability in the response variable that is explained by the explanatory variables. The coefficient of determination is closely related to the test statistic F for testing f3. = f32 = ... = f3" = O. In fact, R2 can be expressed as a function of F. In the case of simple regression, R2 is equal to the square of the sample correlation between X and Y. code 128 excel add in windows Create Barcodes With (Or Without) Excel VBA
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