A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression from a data set of 40 different sharewares that he has developed: SUMMARY OUTPUT Regression Statistics Multiple R 0.843558113 R Square 0.71159029 Adjusted R Square 0.704000561 Standard Error 65.23146731 Observations 40 ANOVA of SS MS F Significance F Regression 1 398949.5945 398949.6 93.757 8.29782E-12 Residual 38 161695.4845 4255.144 Total 39 560645.079 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept -39.4196422 33.20012329 -1.18733 0.24247 -106.629778 27.790494 No of Downloads 3.791124593 0.391531034 9.68282 8.3E-12 2.998511453 4.5837377 Which of the following statement of the correlation coefficient is correct?Select one: The correlation coefficient is 0.71159, which shows a moderate positive nonlinear relationship between the revenue and number of downloads. O The correlation coefficient is 0.8436, which shows a strong positive linear relationship between the revenue and number of downloads. O The correlation coefficient is 0.71159, which shows a strong positive nonlinear relationship between the revenue and number of downloads. O The correlation coefficient is 0.71159, which shows a moderate positive linear relationship between the revenue and number of downloads. O The correlation coefficient is -0.8436, which shows a moderate negative linear relationship between the revenue and number of downloads. Check