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 not complete output from a simple linear regressionalong with the residual plot and normal probabilityplot obtained from a dataset of 30 different sharewares that he has developed:
R Square 0.7554
Adjusted R Square 0.7467
df SS MS F Significance F
Regression 1 171062.9193 171062.9193 86.4759
Total 29 226451.3503
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept -95.0614 26.9183 -3.5315 0.0015 -150.2009 -39.9218
Download 3.7297 0.4011
1) Referring to Table 13-11, what is the standard deviationaround the regression line?
2) Referring to Table 13-11, conduct t-testwhether there is a linear relationship between revenue and the number of downloads? Use p-value and alpha =.05
3) Referring to Table 13-11, what are, respectively, the lower and upper limits of the 95% confidence intervalestimate for population slope?
1. standard deviation around the regression line(standard error of the estimate): sqrt(1978.1582)=44.47649042
2. Ho: r=0
Ha: r is not equal to 0.
this is a two tailed t test.
Regression analysis of computer software is examined.