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Linear regression using Analysis Toolpak

MULTIPLE LINEAR REGRESSION USING THE ANALYSIS TOOLPAK... [Pg.216]

Linear regression can also be performed using the Add-In package called the Analysis ToolPak. Choose Data Analysis... from the Tools menu if the Data Analysis... command is not present in the Tools menu, you must use the Add-Ins... command in the Tools menu to install it. [Pg.216]

Table 9-19 shows the regression analysis performed by Excel using the available Add-In functionality ToolPak. In Table 9-19, the y value of 4.6% was calculated using the 1.0% standard (y = mx + b), where x is the concentration of the 1.0% standard and acceptance criteria given in Table 9-17 of <5.0% was met. In Table 9-19, the %RSD (standard error/y) was calculated as 2.1%, and this had met the acceptance criterion of <4.6% given in Table 9-17. In order to identify if there are significant deviations from the assumed linearity, an investigation of the residuals should also be performed this is demonstrated in Figure 9-6. The residuals were randomly distributed around a true mean of zero. Table 9-19 shows the regression analysis performed by Excel using the available Add-In functionality ToolPak. In Table 9-19, the y value of 4.6% was calculated using the 1.0% standard (y = mx + b), where x is the concentration of the 1.0% standard and acceptance criteria given in Table 9-17 of <5.0% was met. In Table 9-19, the %RSD (standard error/y) was calculated as 2.1%, and this had met the acceptance criterion of <4.6% given in Table 9-17. In order to identify if there are significant deviations from the assumed linearity, an investigation of the residuals should also be performed this is demonstrated in Figure 9-6. The residuals were randomly distributed around a true mean of zero.

See other pages where Linear regression using Analysis Toolpak is mentioned: [Pg.499]    [Pg.349]    [Pg.349]    [Pg.474]   
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