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Based on the tables and graphs below, interpret and report the results. You need to identify the test, discuss the assumptions, follow the decision map steps for interpretation, and then report the results in an academic style. Model 1 Variables Entered/Removed Variables Entered Model 1 Distance in kms from nearest competitor Variables. Removed a. Dependent Variable: Value of monthly sales in $k in 2007 b. All requested variables entered. Sum of Squares 68133866.85 Method Enter 48606508.07 116740374.9 ANOVA df 1 12 13 Model 1 Regression Residual Total a. Dependent Variable: Value of monthly sales in $k in 2007 b. Predictors: (Constant), Distance in kms from nearest competitor Mean Square 68133866.85 4050542.340 R 764 Model Summary F 16.821 R Square 584 549 a. Predictors: (Constant), Distance in kms from nearest competitor b. Dependent Variable: Value of monthly sales in Skin 2007 Sig. Adjusted R Square .001 Std. Error of the Estimate 2012.59592

Based on the tables and graphs below, interpret and report the results. You need to identify the test, discuss the assumptions, follow the decision map steps for interpretation, and then report the results in an academic style. Model 1 Variables Entered/Removed Variables Entered Model 1 Distance in kms from nearest competitor Variables. Removed a. Dependent Variable: Value of monthly sales in $k in 2007 b. All requested variables entered. Sum of Squares 68133866.85 Method Enter 48606508.07 116740374.9 ANOVA df 1 12 13 Model 1 Regression Residual Total a. Dependent Variable: Value of monthly sales in $k in 2007 b. Predictors: (Constant), Distance in kms from nearest competitor Mean Square 68133866.85 4050542.340 R 764 Model Summary F 16.821 R Square 584 549 a. Predictors: (Constant), Distance in kms from nearest competitor b. Dependent Variable: Value of monthly sales in Skin 2007 Sig. Adjusted R Square .001 Std. Error of the Estimate 2012.59592

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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Based on the tables and graphs below, interpret and report the results. You need to identify the test, discuss the assumptions, follow the decision map steps for interpretation, and then report the results in an academic style. Model 1 Variables Entered/Removed Variables Entered Model 1 Distance in kms from nearest competitor Variables. Removed a. Dependent Variable: Value of monthly sales in $k in 2007 b. All requested variables entered. Regression Residual Sum of Squares 68133866.85 Method Enter 48606508.07 116740374.9 ANOVA df Model 1 1 12 Total 13 a. Dependent Variable: Value of monthly sales in $k in 2007 b. Predictors: (Constant), Distance in kms from nearest competitor Mean Square 68133866.85 4050542.340 R .764 Model Summary F 16.821 R Square 584 549 a. Predictors: (Constant), Distance in kms from nearest competitor b. Dependent Variable: Value of monthly sales in Skin 2007 Sig. Adjusted R Square .001 Std. Error of the Estimate 2012.59592
Transcribed Image Text:Based on the tables and graphs below, interpret and report the results. You need to identify the test, discuss the assumptions, follow the decision map steps for interpretation, and then report the results in an academic style. Model 1 Variables Entered/Removed Variables Entered Model 1 Distance in kms from nearest competitor Variables. Removed a. Dependent Variable: Value of monthly sales in $k in 2007 b. All requested variables entered. Regression Residual Sum of Squares 68133866.85 Method Enter 48606508.07 116740374.9 ANOVA df Model 1 1 12 Total 13 a. Dependent Variable: Value of monthly sales in $k in 2007 b. Predictors: (Constant), Distance in kms from nearest competitor Mean Square 68133866.85 4050542.340 R .764 Model Summary F 16.821 R Square 584 549 a. Predictors: (Constant), Distance in kms from nearest competitor b. Dependent Variable: Value of monthly sales in Skin 2007 Sig. Adjusted R Square .001 Std. Error of the Estimate 2012.59592
Model 1 Coefficients" Frequency Unstandardized Coefficients B Std. Error (Constant) Distance in kms from nearest competitor a. Dependent Variable: Value of monthly sales in $k in 2007 1577.544 922.347 1167.401 224.890 Standardized Coefficients Beta .764 t 1.351 4.101 0 Regression Standardized Residual Sig. 202 001 Histogram Dependent Variable: Value of monthly sales in $k in 2007 Mean-2.15E-16 Std. Dev.-0.961 N-14 Regression Standardized Residual : Regression Standardized Residual Scatterplot Dependent Variable: Value of monthly sales in $k in 2007 : Regression Standardized Predicted Value
Transcribed Image Text:Model 1 Coefficients" Frequency Unstandardized Coefficients B Std. Error (Constant) Distance in kms from nearest competitor a. Dependent Variable: Value of monthly sales in $k in 2007 1577.544 922.347 1167.401 224.890 Standardized Coefficients Beta .764 t 1.351 4.101 0 Regression Standardized Residual Sig. 202 001 Histogram Dependent Variable: Value of monthly sales in $k in 2007 Mean-2.15E-16 Std. Dev.-0.961 N-14 Regression Standardized Residual : Regression Standardized Residual Scatterplot Dependent Variable: Value of monthly sales in $k in 2007 : Regression Standardized Predicted Value
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