Statistics Help (Invoice Question)

#1
Please help!

The manager of the purchasing department of a large banking organization would like to develop a model to predict the amount of time it takes to process invoices. Data are collected from a sample of 30 days, and the number of invoices processed and completion time, in hours, is stored in INVOICE

a) Assuming a linear relationship, use the least-squares method to find the equation for the regression line.
b) Interpret the meaning of the Y-intercept and the slope in this problem.
c) Is it appropriate to use the prediction line developed in (a) to predict the amount of time it would take to process 350 invoices? If so, predict the amount of time it would take to process 350 invoices.
d) Is it appropriate to use the prediction line developed in (a) to predict the amount of time it would take to process 150 invoices? If so, predict the amount of time it would take to process 150 invoices.
e) Determine the coefficient of determination, r2, and interpret its meaning.
f) Construct a 95% confidence interval estimate of the mean processing time for all days in which 150 invoices were processed
g) Construct a 95% prediction interval of the processing time for a day in which 150 invoices were processed.
h) Interpret your results of part F and G. Are they different? Why or why not?
 

vinux

Dark Knight
#2
Please help!

The manager of the purchasing department of a large banking organization would like to develop a model to predict the amount of time it takes to process invoices. Data are collected from a sample of 30 days, and the number of invoices processed and completion time, in hours, is stored in INVOICE

a) Assuming a linear relationship, use the least-squares method to find the equation for the regression line.
b) Interpret the meaning of the Y-intercept and the slope in this problem.
c) Is it appropriate to use the prediction line developed in (a) to predict the amount of time it would take to process 350 invoices? If so, predict the amount of time it would take to process 350 invoices.
d) Is it appropriate to use the prediction line developed in (a) to predict the amount of time it would take to process 150 invoices? If so, predict the amount of time it would take to process 150 invoices.
e) Determine the coefficient of determination, r2, and interpret its meaning.
f) Construct a 95% confidence interval estimate of the mean processing time for all days in which 150 invoices were processed
g) Construct a 95% prediction interval of the processing time for a day in which 150 invoices were processed.
h) Interpret your results of part F and G. Are they different? Why or why not?
What help you need?
question b) to h) is depending on a). And where is the output of a)? ( I am not able to open the INVOICE link)
It will be great if you ask some specific questions.
 
#3
Invoice

I apologize the invoice link didn't work, here is the info:

Please Help

Invoices---Processed Time
149---2.1
60---1.8
188---2.3
19---0.3
201---2.7
58---1
77---1.7
222---3.1
181---2.8
30---1
110---1.5
83---1.2
60---0.8
25---0.4
173---2
169---2.5
190---2.9
233---3.4
289---4.1
45---1.2
193---2.5
70---1.8
241---3.8
103---1.5
163---2.8
120---2.5
201---3.3
135---2
80---1.7
29---0.5
 
Last edited:

Mean Joe

TS Contributor
#4
You can use Excel to get a least-squares fit.

See attached. You basically make a scatter plot of your data, and to add trendline you 1) click on the graph to make it active, 2) in menu bar go to Chart > Add Trendline

Now you can get started on answering your questions. Come back if you still have questions.