An accountant for a large department store would like to develop a model to pred
ID: 3350584 • 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
What is the independent variable, X, in this regression?
Select one:
a. Number of invoices processed
b. Time (hours)
c. Intercept
d. None of these
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
Correct option:
a. Number of invoices processed
EXPLANATION:
Given:
Model to predict the amount of time it takes.
In a regression analysis, the variable (x) which is varied for studying its impact on the variable of interest is the independent variable.
Here, the number of invoices processed is the variable that is varied. So, it is the independent variable.
Its impact on the completion time is being studied. So, it is the dependent variable.
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