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Based on these regression results from Lab 5.2 Excel, Evaluating the Relationsh...

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Based on these regression results from Lab 5.2 Excel, Evaluating the Relationship Between Sales and R&D Expenditures: Testing for a Nonlinear Relationship, how can the relationship between sales and R&D be best explained?

Under regression statistics, the following values are shown: Multiple R, 0.909478. R square, 0.827151. Adjusted R square, 0.823859. Standard error, 6030121. Observations, 108. In the ANOVA table at the center, values are shown as follows: Regression: d f, 2. S S, 1.82709E + 16. M S, 9.14E + 15. F, 251.2333. Significance F, 9.49532E minus 41. Residual: d f, 105. S S, 3.81805E + 15. M S, 3.64E + 13. Total: d f, 107. S S, 2.20889E + 16 In the table at the bottom, the entries are shown as follows: Intercept: Coefficients, 21367225. Standard error, 2269617.303. t Stat, 9.414462. P value, 1.26E minus 15. Lower 95 percent, 16866993.19. R and D expenditures: Coefficients, 5.501598. Standard error, 1.980307943. t Stat, 2.778153. P value, 0.006477. Lower 95 percent, 1.575013356. R and D expenditures squared: Coefficients, 1.31E minus 06. Standard error. 3.89595E-07. t Stat, 3.351151. P value, 0.001119. Lower 95 percent, 5.33096E minus 07

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