Math533-Cource Project Part C Essay

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Professor: œ Math 533: Applied Managerial Statistics Course Project Part C: Regression and Correlation Analysis This is the scatter plot of Credit Balance($) vs. Size. It shows the slope of the ‘best fit’ line and indicates that the Credit Balance($) varies directly when Size changes. Credit Balance also increases when Size increases. The following is the MiniTab output: Regression Analysis: Credit Balance($) versus Size The regression equation is Credit Balance($) = 2591 + 403 Size Predictor Coef SE Coef T P Constant 2591.4 195.1 13.29 0.000 Size 403.22 50.95 7.91 0.000 S = 620.162 R-Sq = 56.6% R-Sq(adj) = 55.7% Analysis of Variance Source DF SS MS F P Regression 1 24092210 24092210 62.64 0.000 Residual Error 48 18460853 384601 Total 49 42553062 Predicted Values for New Observations New Obs Fit SE Fit 95% CI 95% PI 1 4607.5 119.0 (4368.2, 4846.9) (3337.9, 5877.2) Values of Predictors for New Observations New Obs Size 1 5.00 The equation of the “best fit” helps describe the relationship between Credit Balance and Size: Credit Balance ($) = 2591 + 403.2 Size Pearson correlation of Credit Balance ($) and Size = 0.752 P-Value = 0.000 The coefficient of correlation is r = 0.752 and the correlation coefficients between the variables show a positive sign and a direct relationship. The correlation coefficient is much greater than the P-Value of 0.000. The p-value of 0.000 is low, which means that there is a very low chance that Credit Balance and Size results are coincidence. The coefficient of determination, R-Sq = 0.566. The proportion of variability in a dataset that is accounted for by the regression model is given by the coefficient of

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