Kizspy | Question: 74
(Choose 1 answer)
(See picture)
A. (i)
B. (ii)
C. (iii)
D. (iv)
NJOVERFLOW.LOD
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 along with
the residual plot and normal probability plot obtained from a data set of 30
different sharewares that he has developed:
Multiple R
RSquare
Regression Statistics
Adjusted R Square
Standard Error
Observations
ANOVA
0.8691
0.7554
0.7467
44.4765
30.0000
Regression
Residual
Total
1
SS
171062 9193
28
55388 4309
MS
171062 9193
1978. 1582
F
86.4759
Significance F
0.0000
29
226451.3503
Coefficients
Intercept
Download
-95.0614
3.7297
Standard Error
26.9183
0.4011
t Stat
P-value
Lower 95%
-3.5315
9.2992
0.0015
0.0000
-150.2009
2.9082
Upper 95%
-39.9218
4.5513
Which of the following is the correct alternative hypothesis for testing whether
there is a linear relationship between revenue and the number of downloads?
(i) H₁b=0
(ii) H₁: b₁ = 0
(iii) H₁₁ =0
(iv) H₁₁ = 0
