Which of the following is the correct interpretation for the slope coefficient?

MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
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20 - 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:
Which of the following is the correct interpretation for the slope coefficient?
Regression Statistics
Multiple R
RSquare
Adjusted R Square
Standard Error
Observations
0.8691
0.7554
0.7467
44.4765
30.0000
ANOVA
df
S
171062.9193 171062.9193
MS
Regression
Residual
Significance F
0.0000
86.4759
28
55388.4309
1978.1582
Total
29
226451.3503
Coefficients
-95.0614
Standard Error
26.9183
t Stat
-3.5315
Upper 95%
39.9218
4 5513
P-value
Lower 95%
150.2009
Intercept
Download
0.0015
3.7297
0.4011
9.2992
0.0000
2.9082
Download Residual Plot
120
100
80
60
40
20
-20
-40
-60
-80
-100
Residuals
Transcribed Image Text:20 - 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: Which of the following is the correct interpretation for the slope coefficient? Regression Statistics Multiple R RSquare Adjusted R Square Standard Error Observations 0.8691 0.7554 0.7467 44.4765 30.0000 ANOVA df S 171062.9193 171062.9193 MS Regression Residual Significance F 0.0000 86.4759 28 55388.4309 1978.1582 Total 29 226451.3503 Coefficients -95.0614 Standard Error 26.9183 t Stat -3.5315 Upper 95% 39.9218 4 5513 P-value Lower 95% 150.2009 Intercept Download 0.0015 3.7297 0.4011 9.2992 0.0000 2.9082 Download Residual Plot 120 100 80 60 40 20 -20 -40 -60 -80 -100 Residuals
Download
3.7297
0.4011
9.2992
0.0000
2.9082
4.5513
Download Residual Plot
120
100
80
60
40
-20
-40
60
-80
-100
0.00
20.00
40.00
60.00
80.00
100.00
120.00
Download
a) O For each increase of 1 thousand dollars in expected revenue, the expected number of downloads is estimated
to increase by 3.7297 thousands.
b) For each decrease of 1 thousand downloads, the expected revenue is estimated to increase by $ 3.7297
thousands.
C) For each increase of 1 thousand downloads, the expected revenue is estimated to increase by $ 3.7297
thousands.
d)
For each decrease of 1 thousand dollars in expected revenue, the expected number of downloads is estimated
to increase by 3.7297 thousands.
Residuals
Transcribed Image Text:Download 3.7297 0.4011 9.2992 0.0000 2.9082 4.5513 Download Residual Plot 120 100 80 60 40 -20 -40 60 -80 -100 0.00 20.00 40.00 60.00 80.00 100.00 120.00 Download a) O For each increase of 1 thousand dollars in expected revenue, the expected number of downloads is estimated to increase by 3.7297 thousands. b) For each decrease of 1 thousand downloads, the expected revenue is estimated to increase by $ 3.7297 thousands. C) For each increase of 1 thousand downloads, the expected revenue is estimated to increase by $ 3.7297 thousands. d) For each decrease of 1 thousand dollars in expected revenue, the expected number of downloads is estimated to increase by 3.7297 thousands. Residuals
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