An accountant for a large department store has the business objective of develop

Question

An accountant for a large department store has the business objective of developing a model to predict the amount of time it takes to process invoices based on the number of invoices. Data are collected from the past 32 working days, and the number of invoices processed and completion time (in hours) are stored here. What are the values for (1) the sum of squares Y (2) the sum of squares error (3) the sum of squares predicted (4) the proportion of variation in completion time that is explained by the number of invoices processed (5) the lower limit of the 95% confidence interval estimate for the population slope B (6) the upper limit of the 95% confidence interval estimate for the population slope B (7) the intercept A (8) the slope b (9) the standard error of estimate and (10) the predicted amount of time it would take to process 150 invoices Hint: Use PHStat to obtain all the values and answers should be accurate to 4 decimal places.

Explanation / Answer

You are given the y=time and x=invoice

Here you have to find the regression equation and other part.

In excel Go to >>Data >>> Data Analysis >>>>Regression >>>Input range y= Drag all values of y and Input range of x = drag all values of x >>>>and click OK. you get following output.

32

0.014119

1) Sum of square of y =25.3511

3) sum of square of predicted =4.048

4) Proportion of variation =R^2=0.8622

5)

Lower limit=

6) Upper limit=

7) y intercept =0.4872

8)slope (b)=0.0123

9) Standerd error=

0.13142

10) You get regression equation is

time=0.4872+0.01229*invoice

you have to predict time for invoice 150 so just plug value in above equation

time= 0.4842+0.01229*150=2.3277

Regression Statistics Multiple R 0.928597392 R Square 0.862293116 Adjusted R Square 0.857702886 Standard Error 0.3673572 Observations

32

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