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Model Summary Adjusted R Square Std. Error of the Estimate Model R. R Square 1 .772" .596 .516 215.1509 a. Predictors: (Constant), Porosity ANOVA Sum of Model Squares df Mean Square Sig. 1 Regression 341943.282 1 341943.282 7.387 .042 Residual 231449.575 46289.915 Total 573392.857 6. a. Dependent Variable: Runoff b. Predictors: (Constant), Porosity Coefficients" Standardized Unstandardized Coefficients Coefficients Model B Std. Error Beta Sig. 1 (Constant) 1863.761 237.546 7.846 .001 Porosity -80.729 29.703 -.772 -2.718 .042 a. Dependent Variable: Runoff A geomorphologist is building a model to understand variation in the amount of runoff observed in various streams within a large drainage basin. Linear regression is used to determine whether runoff is inversely related to the porosity of the soil. The variables here are thus runoff and porosity. The SPSS output from the analysis is shown above. One of the cases has a runoff value of 900 and a porosity value of 8. Calculate the value of the residual for this case.

Model Summary Adjusted R Square Std. Error of the Estimate Model R. R Square 1 .772" .596 .516 215.1509 a. Predictors: (Constant), Porosity ANOVA Sum of Model Squares df Mean Square Sig. 1 Regression 341943.282 1 341943.282 7.387 .042 Residual 231449.575 46289.915 Total 573392.857 6. a. Dependent Variable: Runoff b. Predictors: (Constant), Porosity Coefficients" Standardized Unstandardized Coefficients Coefficients Model B Std. Error Beta Sig. 1 (Constant) 1863.761 237.546 7.846 .001 Porosity -80.729 29.703 -.772 -2.718 .042 a. Dependent Variable: Runoff A geomorphologist is building a model to understand variation in the amount of runoff observed in various streams within a large drainage basin. Linear regression is used to determine whether runoff is inversely related to the porosity of the soil. The variables here are thus runoff and porosity. The SPSS output from the analysis is shown above. One of the cases has a runoff value of 900 and a porosity value of 8. Calculate the value of the residual for this case.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Model Summary Adjusted R Square Std. Error of Model R R Square the Estimate 1 .772 .596 .516 215.1509 a. Predictors: (Constant), Porosity ANOVA Sum of Model Squares df Mean Square F Sig. Regression 341943.282 1 341943.282 7.387 .042b Residual 231449.575 46289.915 Total 573392.857 a. Dependent Variable: Runoff b. Predictors: (Constant), Porosity Coefficients Standardized Unstandardized Coefficients Coefficients Model B Std. Error Beta t Sig. (Constant) 1863.761 237.546 7.846 .001 Porosity -80.729 29.703 -.772 -2.718 .042 a. Dependent Variable: Runoff A geomorphologist is building a model to understand variation in the amount of runoff observed in various streams within a large drainage basin. Linear regression is used to determine whether runoff is inversely related to the porosity of the soil. The variables here are thus runoff and porosity. The SPSS output from the analysis is shown above. One of the cases has a runoff value of 900 and a porosity value of 8. Calculate the value of the residual for this case.
Transcribed Image Text:Model Summary Adjusted R Square Std. Error of Model R R Square the Estimate 1 .772 .596 .516 215.1509 a. Predictors: (Constant), Porosity ANOVA Sum of Model Squares df Mean Square F Sig. Regression 341943.282 1 341943.282 7.387 .042b Residual 231449.575 46289.915 Total 573392.857 a. Dependent Variable: Runoff b. Predictors: (Constant), Porosity Coefficients Standardized Unstandardized Coefficients Coefficients Model B Std. Error Beta t Sig. (Constant) 1863.761 237.546 7.846 .001 Porosity -80.729 29.703 -.772 -2.718 .042 a. Dependent Variable: Runoff A geomorphologist is building a model to understand variation in the amount of runoff observed in various streams within a large drainage basin. Linear regression is used to determine whether runoff is inversely related to the porosity of the soil. The variables here are thus runoff and porosity. The SPSS output from the analysis is shown above. One of the cases has a runoff value of 900 and a porosity value of 8. Calculate the value of the residual for this case.
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