Kevin Bulley
Math 125
Project 3
Introduction
Statcrunch provided data on a study 2015 study that measured the correlation of base salary vs guaranteed salary of Major League Soccer players. The study of Major League Soccer players' salaries had a sample size of 570 players. The soccer players' base salary was the independent variable. The soccer players guaranteed compensation/salary was noted as the dependent variable.
Analysis
The regression equation in table two is 2015 Guaranteed Compensation = 3006.9887 + 1.0928 2015 Base Salary. The correlation coefficient (variable R) is 0.9933. The coefficient of determination (R^2) is 0.9867. The coefficient determination suggest that 98.67% of the change in 2015 guaranteed compensation to based salary can be explained by the regression equation in the independent variable.
Conclusion
In summary, the independent variable was the soccer player’s base salary. The dependent variable was the guaranteed compensation and the sample size is 570 players. The results of the simple linear regression graph shows that there is a strong positive correlation between guaranteed salary and based salary. With the cluster points within the graph falling closely by the regression line. The strong positive correlation coefficient, 0.9933 indicates that it is an appropriate way of determining the data’s regression.
Simple linear regression results:Dependent Variable: 2015 Guaranteed Compensation Independent Variable: 2015 Base Salary 2015 Guaranteed Compensation = 3006.9887 + 1.0928344 2015 Base Salary Sample size: 570 R (correlation coefficient) = 0.99332467 Rsq = 0.9866939 Estimate of error standard deviation: 92788.37 Parameter estimates:
Analysis of variance table for regression model:

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