Model Variables Entered/Removedª Variables Removed Method Enter Variables Entered Model Distance in kms from nearest competitor a. Dependent Variable: Value of monthly sales in $k in 2007 b. All requested variables entered. ANOVAª Model 1 Sum of Squares Regression 68133866.85 1 Residual 48606508.07 12 Total 116740374.9 13 a. Dependent Variable: Value of monthly sales in $k in 2007 b. Predictors: (Constant), Distance in kms from nearest competitor df R .764ª Mean Square 68133866.85 4050542.340 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 $k in 2007 Sig. Adjusted R Square .001b Std. Error of the Estimate 2012.59592

MATLAB: An Introduction with Applications
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Chapter1: Starting With Matlab
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Please please how to write if based on the following IF Based on the tables and graphs below, interpret and report the results. You need to identify the test, discuss the assumption of normality only, follow the decision map steps for interpretation, and then report the results in an academic style. 

Model
Variables Entered/Removedª
Variables
Removed
Variables
Entered
Model
Distance in
kms from
nearest
competitor
Method
Enter
a. Dependent Variable: Value of monthly sales
in $k in 2007
b. All requested variables entered.
ANOVA
Model
1
Sum of
Squares
Mean Square
Regression
68133866.85
1
68133866.85
Residual
48606508.07
12 4050542.340
Total
116740374.9
13
a. Dependent Variable: Value of monthly sales in $k in 2007
b. Predictors: (Constant), Distance in kms from nearest competitor
df
R
.764ª
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 $k in 2007
Sig.
Adjusted R
Square
.001b
Std. Error of
the Estimate
2012.59592
Transcribed Image Text:Model Variables Entered/Removedª Variables Removed Variables Entered Model Distance in kms from nearest competitor Method Enter a. Dependent Variable: Value of monthly sales in $k in 2007 b. All requested variables entered. ANOVA Model 1 Sum of Squares Mean Square Regression 68133866.85 1 68133866.85 Residual 48606508.07 12 4050542.340 Total 116740374.9 13 a. Dependent Variable: Value of monthly sales in $k in 2007 b. Predictors: (Constant), Distance in kms from nearest competitor df R .764ª 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 $k in 2007 Sig. Adjusted R Square .001b Std. Error of the Estimate 2012.59592
Model
Frequency
(Constant)
Distance in kms from
nearest competitor
a. Dependent Variable: Value of monthly sales in $k in 2007
3
N
1
0
2
Coefficients
Unstandardized Coefficients
B Std. Error
1577.544
922.347
-1
1167.401
224.890
Standardized
Coefficients
Beta
0
.764
Histogram
Dependent Variable: Value of monthly sales in $k in 2007
1
1.351
4.101
Regression Standardized Residual
Sig.
202
.001
2
Mean = -2.15E-16
Std. Dev. 0.961
N=14
Transcribed Image Text:Model Frequency (Constant) Distance in kms from nearest competitor a. Dependent Variable: Value of monthly sales in $k in 2007 3 N 1 0 2 Coefficients Unstandardized Coefficients B Std. Error 1577.544 922.347 -1 1167.401 224.890 Standardized Coefficients Beta 0 .764 Histogram Dependent Variable: Value of monthly sales in $k in 2007 1 1.351 4.101 Regression Standardized Residual Sig. 202 .001 2 Mean = -2.15E-16 Std. Dev. 0.961 N=14
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