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An accountant wishes to predict direct labor cost ( y ) on the basis of the batc

ID: 3388466 • Letter: A

Question

An accountant wishes to predict direct labor cost (y) on the basis of the batch size (x) of a product produced in a job shop. Data for 12 production runs are given in the table below, along with the Excel output from fitting a least squares regression line to the data.

  

  
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Find b1 and b0. (Round your intermediate value and final answers to 4 decimal places. Negative amounts should be indicated by a minus sign.)

  

  b1 is the estimated

in for every 1 unit increase in
  

.

  b0 is the estimated

when = 0;

.

Write the least squares prediction equation. (Round your answers to 4 decimal places. Negative amounts should be indicated by a minus sign.)

Use the least squares line to obtain a point estimate of the mean direct labor cost for all batches of size 60 and a point prediction of the direct labor cost for an individual batch of size 60. (Round your answer to 3 decimal places.)

Direct Labor Cost Data Direct Labor
Cost, y ($100s) Batch
Size, x 625 14 700 17 559 28 313 18 922 55 571 79 432 58 852 91 462 66 764 78 235 33 167 58

Explanation / Answer

An accountant wishes to predict direct labor cost (y) on the basis of the batch size (x) of a product produced in a job shop. Data for 12 production runs are given in the table below, along with the Excel output from fitting a least squares regression line to the data.

  

Direct Labor Cost Data

Direct Labor
Cost, y ($100s)

Batch
Size, x

625

14

700

17

559

28

313

18

922

55

571

79

432

58

852

91

462

66

764

78

235

33

167

58

  

Regression Analysis

0.085

n

12

r

0.291

k

1

Std. Error

239.678

Dep. Var.

cost(y)

ANOVA table

Source

SS

df

MS

F

p-value

Regression

53,328.3047

1  

53,328.3047

0.93

.3580

Residual

574,453.3620

10   

57,445.3362

Total

627,781.6667

11  

Regression output

confidence interval

variables

coefficients

std. error

   t (df=10)

p-value

95% lower

95% upper

Intercept

421.2999

150.5849

2.798

.0189

85.7759

756.8240

size(x)

2.5990

2.6975

0.963

.3580

-3.4113

8.6093

Predicted values for: cost(y)

95% Confidence Interval

95% Prediction Interval

size(x)

Predicted

lower

upper

lower

upper

Leverage

60

577.240

410.849

743.630

17.884

1,136.595

0.097


(a)

Find b1 and b0. (Round your intermediate value and final answers to 4 decimal places. Negative amounts should be indicated by a minus sign.)

  

  b1   = 2.5990

  b0 = 421.2999

(b)

Interpret the meanings of b0 and b1. Does the interpretation of b0 make practical sense?

  b1 is the estimated

in for every 1 unit increase in size, the increase in cost(in 100s)
  

.

  b0 is the estimated

when size x = 0;

No, the interpretation of b0 make no practical sense

.

(c)

Write the least squares prediction equation. (Round your answers to 4 decimal places. Negative amounts should be indicated by a minus sign.)

   Y = 421.2999 + 2.5990 x

(d)

Use the least squares line to obtain a point estimate of the mean direct labor cost for all batches of size 60 and a point prediction of the direct labor cost for an individual batch of size 60. (Round your answer to 3 decimal places.)


   y(60) = 577.240 hundreds of dollars.

Direct Labor Cost Data

Direct Labor
Cost, y ($100s)

Batch
Size, x

625

14

700

17

559

28

313

18

922

55

571

79

432

58

852

91

462

66

764

78

235

33

167

58

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