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Multiple Regression call: 1m(formula Energy Bar Sprice - Energy_BarScalories + Energy_Bar Sprotein + Energy Bar$Fat) Residuals: Min 1Q Median 3Q Max -0.52712 -0.18270 -0.09316 0.23599 0.47918 Coefficients: (Intercept) 0.936 Estimate Std. Error t value Pr(>\t]) -0.062159 0.757488 -0.082 Energy BarScalories 0.002590 0.002916 0.888 Energy BarSProtein 0.048206 0.029663 1.625 0.132 Energy Bar$Fat 0.043968 0.048908 0.899 0.388 0.393 Residual standard error: 0.3165 on 11 degrees of freedom Multiple R-squared: 0.392, Adjusted R-squared: 0.2262 F-statistic: 2.364 on 3 and 11 DF, p-value: 0.127 a. Interpret each of the results presented in the output and provide an interpretation for each of them. b. Using a significance level of 0.05, determine whether the data support the hypothesis of a linear relationship between dependent and independent variables.

Multiple Regression call: 1m(formula Energy Bar Sprice - Energy_BarScalories + Energy_Bar Sprotein + Energy Bar$Fat) Residuals: Min 1Q Median 3Q Max -0.52712 -0.18270 -0.09316 0.23599 0.47918 Coefficients: (Intercept) 0.936 Estimate Std. Error t value Pr(>\t]) -0.062159 0.757488 -0.082 Energy BarScalories 0.002590 0.002916 0.888 Energy BarSProtein 0.048206 0.029663 1.625 0.132 Energy Bar$Fat 0.043968 0.048908 0.899 0.388 0.393 Residual standard error: 0.3165 on 11 degrees of freedom Multiple R-squared: 0.392, Adjusted R-squared: 0.2262 F-statistic: 2.364 on 3 and 11 DF, p-value: 0.127 a. Interpret each of the results presented in the output and provide an interpretation for each of them. b. Using a significance level of 0.05, determine whether the data support the hypothesis of a linear relationship between dependent and independent variables.

College Algebra
College Algebra
7th Edition
ISBN:9781305115545
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:James Stewart, Lothar Redlin, Saleem Watson
Chapter1: Equations And Graphs
Section: Chapter Questions
Problem 5P
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Multiple Regression Call: 1m (formula Energy Bar SPrice Energy BarScalories + Energy Bar $Protein + Energy Bar$Fat) Residuals: Min 1Q Median 3Q Max -0.52712 -0.18270 -0.09316 0.23599 0.47918 Coefficients: (Intercept) Estimate Std. Error t value Pr(>\t]) -0.062159 0.757488 -0.082 Energy BarScalories 0.002590 0.002916 Energy BarSProtein 0.048206 0.029663 Energy Bar$Fat 0.888 1.625 0.043968 0.048908 0.899 0.936 0.393 0.132 0.388 Residual standard error: 0.3165 on 11 degrees of freedom Multiple R-squared: 0.392, Adjusted R-squared: 0.2262 F-statistic: 2.364 on 3 and 11 DF, p-value: 0.127 a. Interpret each of the results presented in the output and provide an interpretation for each of them. b. Using a significance level of 0.05, determine whether the data support the hypothesis of a linear relationship between dependent and independent variables.
Transcribed Image Text:Multiple Regression Call: 1m (formula Energy Bar SPrice Energy BarScalories + Energy Bar $Protein + Energy Bar$Fat) Residuals: Min 1Q Median 3Q Max -0.52712 -0.18270 -0.09316 0.23599 0.47918 Coefficients: (Intercept) Estimate Std. Error t value Pr(>\t]) -0.062159 0.757488 -0.082 Energy BarScalories 0.002590 0.002916 Energy BarSProtein 0.048206 0.029663 Energy Bar$Fat 0.888 1.625 0.043968 0.048908 0.899 0.936 0.393 0.132 0.388 Residual standard error: 0.3165 on 11 degrees of freedom Multiple R-squared: 0.392, Adjusted R-squared: 0.2262 F-statistic: 2.364 on 3 and 11 DF, p-value: 0.127 a. Interpret each of the results presented in the output and provide an interpretation for each of them. b. Using a significance level of 0.05, determine whether the data support the hypothesis of a linear relationship between dependent and independent variables.
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