Scatter Plot
My scatter plot has no correlation and my two variables are walmart and target incidents. There are no outliers. There is no linear relationship either.
My signifigance level is .05 because the variation is moderate. Weak correlation
My line of best fit is y=171.28464x + .0044184021
Simple linear regression results:
Dependent Variable: Target Incidents
Independent Variable: Walmart Incidents
Target Incidents = 171.28464 + 0.0044184021 Walmart Incidents
Sample size: 32
R (correlation coefficient) = 0.0069340322
Rsq = 0.000048080803
Estimate of error standard deviation: 100.76015
Parameter estimates:
Parameter  Estimate  Std. Err.  Alternative  DF  TStat  Pvalue 

Intercept  171.28464  91.3491  ≠ 0  30  1.8750556  0.0705 
Slope  0.0044184021  0.11633444  ≠ 0  30  0.037980172  0.97 
Analysis of variance table for regression model:
Source  DF  SS  MS  Fstat  Pvalue 

Model  1  14.64507  14.64507  0.0014424934  0.97 
Error  30  304578.23  10152.608  
Total  31  304592.88 
Y intercept is 171.28464
Correlation Coefficient is .0069340322
Slope is .0044184021
R squared is .0000448080803
My line of best fit doesn't seem to touch any of the point because there is no correlation. My terms are significant.
Graph with line of best fit
The line of best fit doesn't seemt to work with this data becaue there is no correlation. My points are not correlated and there is no relation.
EC 1 Yes on the residuals graph they seem to follow a normal distribution.
EC 3 Yes I got different results.
EC 2 The graph is still similar with no correlation.
EC 5 Multiple linear regression graph
Simple linear regression results:
Dependent Variable: Target Incidents Independent Variable: Walmart Incidents Target Incidents = 171.28464 + 0.0044184021 Walmart Incidents Sample size: 32 R (correlation coefficient) = 0.0069340322 Rsq = 0.000048080803 Estimate of error standard deviation: 100.76015 Parameter estimates:
Analysis of variance table for regression model:

Multiple linear regression results:
Dependent Variable: Walmart Incidents Independent Variable(s): Target Incidents, Distance, Difference Walmart Incidents = 1.8189894e12 + 1 Target Incidents + 1.1368684e13 Distance + 1 Difference Parameter estimates:
Analysis of variance table for multiple regression model:
Summary of fit: Root MSE: 3.8117801e12 Rsquared: 1 Rsquared (adjusted): 1 
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Nov 13, 2017
When determine whether a slope is significant or not, we compare the Pvalue with the significance level;
R^2 is the percentage of variance explained by linear model;
The multiple linear regression model is useless since we know that Walmart Incidents=Target Difference