20
(Choose 1 answer)
(See picture)
A. (iv)
B. (i)
C. (iii)
D. (ii)
A computer software developer would like to use the number of downloads (inthousands) 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 along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed:
Regression Statistics
Multiple R
RSquare
Adjusted R Square
Standard Error
Observations
0.8691
0.7554
0.7467
44.4765
30.0000
ANOVA
Regression
Residual
Total
SS
MS
1
28
171062 9193 171062 9193
55388.4309
1978. 1582
29 226451.3503
F
86.4759
Significance F
0.0000
Coefficients
Standard Error
Intercept
Download
-95.0614
3.7297
26.9183
0.4011
t Stat
-3.5315
9.2992
P-value
0.0015
0.0000
Lower 95%-150.2009
2.9082
Upper 95%
-39.9218
4.5513
Which of the following is the correct alternative hypothesis for testing whether
