An accountant for a large department store would like to develop a model to pred
ID: 3350937 • Letter: A
Question
An accountant for a large department store would like to develop a model to predict the amount of time it takes to process invoices. Data are collected from the 30 working days and the number of invoices processed and completion time (in hours) are used to obtain the following PHStat output.
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.945
R Square
0.892
Adjusted R Square
0.889
Standard Error
0.334
Observations
30
ANOVA
df
SS
MS
F
Significance F
Regression
1
25.944
25.944
232.220
4.3946E-15
Residual
28
3.128
0.112
Total
29
29.072
Coefficients
Standard Error
t Stat
P-value
Intercept
0.402
0.124
3.256
0.003
Invoices Processed
0.013
0.001
15.239
0.000
The amount of time it would take to process 100 invoices is Answer hours. (to three decimal places)
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.945
R Square
0.892
Adjusted R Square
0.889
Standard Error
0.334
Observations
30
ANOVA
df
SS
MS
F
Significance F
Regression
1
25.944
25.944
232.220
4.3946E-15
Residual
28
3.128
0.112
Total
29
29.072
Coefficients
Standard Error
t Stat
P-value
Intercept
0.402
0.124
3.256
0.003
Invoices Processed
0.013
0.001
15.239
0.000
Explanation / Answer
Regression equation:
y = 0.402 + 0.013x
For x = 100,
y = 0.402 + 0.013(100)
y = 1.702
Hence,
The amount of time it would take to process 100 invoices = 1.702 hours
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