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Day Hour Temperature Sales Monday 1:00 P.M. to 2:00 P.M. 82 55.49 Monday 2:00 P.

ID: 3203063 • Letter: D

Question

Day Hour Temperature Sales Monday 1:00 P.M. to 2:00 P.M. 82 55.49 Monday 2:00 P.M. to 3:00 P.M. 83 61.89 Monday 3:00 P.M. to 4:00 P.M. 87 44.79 Monday 4:00 P.M. to 5:00 P.M. 93 68.62 Monday 5:00 P.M. to 6:00 P.M. 95 58.82 Monday 6:00 P.M. to 7:00 P.M. 96 51.85 Monday 7:00 P.M. to 8:00 P.M. 93 66.2 Monday 8:00 P.M. to 9:00 P.M. 89 52.89 Monday 9:00 P.M. to 10:00 P.M. 86 61.95 Tuesday 1:00 P.M. to 2:00 P.M. 86 59.55 Tuesday 2:00 P.M. to 3:00 P.M. 90 47.07 Tuesday 3:00 P.M. to 4:00 P.M. 92 53.29 Tuesday 4:00 P.M. to 5:00 P.M. 96 47.42 Tuesday 5:00 P.M. to 6:00 P.M. 99 60.52 Tuesday 6:00 P.M. to 7:00 P.M. 100 71.98 Tuesday 7:00 P.M. to 8:00 P.M. 97 55.71 Tuesday 8:00 P.M. to 9:00 P.M. 94 64.95 Tuesday 9:00 P.M. to 10:00 P.M. 93 60.12 Wednesday 1:00 P.M. to 2:00 P.M. 90 48.72 Wednesday 2:00 P.M. to 3:00 P.M. 94 66.41 Wednesday 3:00 P.M. to 4:00 P.M. 96 65.27 Wednesday 4:00 P.M. to 5:00 P.M. 98 54.76 Wednesday 5:00 P.M. to 6:00 P.M. 100 48.08 Wednesday 6:00 P.M. to 7:00 P.M. 103 53.59 Wednesday 7:00 P.M. to 8:00 P.M. 101 62.99 Wednesday 8:00 P.M. to 9:00 P.M. 98 66.35 Wednesday 9:00 P.M. to 10:00 P.M. 95 67.92 Thursday 1:00 P.M. to 2:00 P.M. 88 47.85 Thursday 2:00 P.M. to 3:00 P.M. 90 56.62 Thursday 3:00 P.M. to 4:00 P.M. 92 46.05 Thursday 4:00 P.M. to 5:00 P.M. 95 56.72 Thursday 5:00 P.M. to 6:00 P.M. 99 69.94 Thursday 6:00 P.M. to 7:00 P.M. 99 65.72 Thursday 7:00 P.M. to 8:00 P.M. 97 51.01 Thursday 8:00 P.M. to 9:00 P.M. 94 73.51 Thursday 9:00 P.M. to 10:00 P.M. 92 65.57 Friday 1:00 P.M. to 2:00 P.M. 90 63.26 Friday 2:00 P.M. to 3:00 P.M. 93 44.09 Friday 3:00 P.M. to 4:00 P.M. 96 65.69 Friday 4:00 P.M. to 5:00 P.M. 99 48.62 Friday 5:00 P.M. to 6:00 P.M. 103 68.16 Friday 6:00 P.M. to 7:00 P.M. 105 67.79 Friday 7:00 P.M. to 8:00 P.M. 104 62.79 Friday 8:00 P.M. to 9:00 P.M. 101 70.16 Friday 9:00 P.M. to 10:00 P.M. 99 68.05 Saturday 1:00 P.M. to 2:00 P.M. 88 60.43 Saturday 2:00 P.M. to 3:00 P.M. 90 63.78 Saturday 3:00 P.M. to 4:00 P.M. 92 67.8 Saturday 4:00 P.M. to 5:00 P.M. 95 69.53 Saturday 5:00 P.M. to 6:00 P.M. 97 61.8 Saturday 6:00 P.M. to 7:00 P.M. 99 57.92 Saturday 7:00 P.M. to 8:00 P.M. 98 53.97 Saturday 8:00 P.M. to 9:00 P.M. 95 71.55 Saturday 9:00 P.M. to 10:00 P.M. 92 57.93 Use a multiple linear regression model with the causal variable outside temperature and dummy variables as follows to develop an equation to account for both seasonal effects and the relationship between outside temperature and hourly sales in the data in the data: Hour1 = 1 if the sales were recorded between 1:00 P.M. and 2:00 P.M., 0 otherwise; Hour2 = 1 if the sales were recorded between 2:00 P.M. and 3:00 P.M., 0 otherwise; . . . Hour8 = 1 if the sales were recorded between 8:00 P.M. and 9:00 P.M., 0 otherwise. Note that when the values of the 8 dummy variables are equal to 0, the observation corresponds to the 9:00 P.M. to 10:00 P.M. hour. If required, round your answers to three decimal places. For subtractive or negative numbers use a minus sign even if there is a + sign before the blank. (Example: -300) Sales = + Temperature + Hour1 + Hour2 + Hour3 + Hour4 + Hour5 + Hour6 + Hour7 + Hour8 Based on this model, compute an estimate of hourly sales for today from 2:00 P.M. to 3:00 P.M. if the temperature at 2:00 P.M. is 93oF. If required, round your answers to two decimal places. $ Is the model you developed in part (b) or the model you developed in part (c) more effective? If required, round your answers to three decimal places. Model developed in part (b) Model developed in part (c) MSE Day Hour Temperature Sales Monday 1:00 P.M. to 2:00 P.M. 82 55.49 Monday 2:00 P.M. to 3:00 P.M. 83 61.89 Monday 3:00 P.M. to 4:00 P.M. 87 44.79 Monday 4:00 P.M. to 5:00 P.M. 93 68.62 Monday 5:00 P.M. to 6:00 P.M. 95 58.82 Monday 6:00 P.M. to 7:00 P.M. 96 51.85 Monday 7:00 P.M. to 8:00 P.M. 93 66.2 Monday 8:00 P.M. to 9:00 P.M. 89 52.89 Monday 9:00 P.M. to 10:00 P.M. 86 61.95 Tuesday 1:00 P.M. to 2:00 P.M. 86 59.55 Tuesday 2:00 P.M. to 3:00 P.M. 90 47.07 Tuesday 3:00 P.M. to 4:00 P.M. 92 53.29 Tuesday 4:00 P.M. to 5:00 P.M. 96 47.42 Tuesday 5:00 P.M. to 6:00 P.M. 99 60.52 Tuesday 6:00 P.M. to 7:00 P.M. 100 71.98 Tuesday 7:00 P.M. to 8:00 P.M. 97 55.71 Tuesday 8:00 P.M. to 9:00 P.M. 94 64.95 Tuesday 9:00 P.M. to 10:00 P.M. 93 60.12 Wednesday 1:00 P.M. to 2:00 P.M. 90 48.72 Wednesday 2:00 P.M. to 3:00 P.M. 94 66.41 Wednesday 3:00 P.M. to 4:00 P.M. 96 65.27 Wednesday 4:00 P.M. to 5:00 P.M. 98 54.76 Wednesday 5:00 P.M. to 6:00 P.M. 100 48.08 Wednesday 6:00 P.M. to 7:00 P.M. 103 53.59 Wednesday 7:00 P.M. to 8:00 P.M. 101 62.99 Wednesday 8:00 P.M. to 9:00 P.M. 98 66.35 Wednesday 9:00 P.M. to 10:00 P.M. 95 67.92 Thursday 1:00 P.M. to 2:00 P.M. 88 47.85 Thursday 2:00 P.M. to 3:00 P.M. 90 56.62 Thursday 3:00 P.M. to 4:00 P.M. 92 46.05 Thursday 4:00 P.M. to 5:00 P.M. 95 56.72 Thursday 5:00 P.M. to 6:00 P.M. 99 69.94 Thursday 6:00 P.M. to 7:00 P.M. 99 65.72 Thursday 7:00 P.M. to 8:00 P.M. 97 51.01 Thursday 8:00 P.M. to 9:00 P.M. 94 73.51 Thursday 9:00 P.M. to 10:00 P.M. 92 65.57 Friday 1:00 P.M. to 2:00 P.M. 90 63.26 Friday 2:00 P.M. to 3:00 P.M. 93 44.09 Friday 3:00 P.M. to 4:00 P.M. 96 65.69 Friday 4:00 P.M. to 5:00 P.M. 99 48.62 Friday 5:00 P.M. to 6:00 P.M. 103 68.16 Friday 6:00 P.M. to 7:00 P.M. 105 67.79 Friday 7:00 P.M. to 8:00 P.M. 104 62.79 Friday 8:00 P.M. to 9:00 P.M. 101 70.16 Friday 9:00 P.M. to 10:00 P.M. 99 68.05 Saturday 1:00 P.M. to 2:00 P.M. 88 60.43 Saturday 2:00 P.M. to 3:00 P.M. 90 63.78 Saturday 3:00 P.M. to 4:00 P.M. 92 67.8 Saturday 4:00 P.M. to 5:00 P.M. 95 69.53 Saturday 5:00 P.M. to 6:00 P.M. 97 61.8 Saturday 6:00 P.M. to 7:00 P.M. 99 57.92 Saturday 7:00 P.M. to 8:00 P.M. 98 53.97 Saturday 8:00 P.M. to 9:00 P.M. 95 71.55 Saturday 9:00 P.M. to 10:00 P.M. 92 57.93

Explanation / Answer

Result:

Sales = + Temperature + Hour1 + Hour2 + Hour3 + Hour4 + Hour5 + Hour6 + Hour7 + Hour8

Sales = 21.83+ 0.45*Temperature + (-5.23)*hour1 + (-5.67)*Hour2 + (-6.29)*Hour3 +( -7.40)*Hour4 + (-5.07)*Hour5 +( -5.49)* Hour6 +( -7.29)* Hour7 + 1.93*Hour8

            

Based on this model, compute an estimate of hourly sales for today from 2:00 P.M. to 3:00 P.M. if the temperature at 2:00 P.M. is 93oF.

             If required, round your answers to two decimal places.

             $57.99

             Is the model you developed in part (b) or the model you developed in part (c) more effective?

             If required, round your answers to three decimal places.

            

             Model developed in part (b)          Model developed i

Se=7.842

Regression Analysis

0.212

Adjusted R²

0.050

n

54

R

0.460

k

9

Std. Error

7.842

Dep. Var.

Sales

ANOVA table

Source

SS

df

MS

F

p-value

Regression

726.2814

9  

80.6979

1.31

.2583

Residual

2,705.9709

44  

61.4993

Total

3,432.2523

53  

Regression output

confidence interval

variables

coefficients

std. error

   t (df=44)

p-value

95% lower

95% upper

Intercept

21.8336

31.7253

0.688

.4949

-42.1046

85.7718

Temperature

0.4498

0.3400

1.323

.1927

-0.2354

1.1350

Hour1

-5.2328

4.8986

-1.068

.2913

-15.1053

4.6398

Hour2

-5.6722

4.6290

-1.225

.2270

-15.0014

3.6569

Hour3

-6.2917

4.5291

-1.389

.1718

-15.4195

2.8360

Hour4

-7.4027

4.6539

-1.591

.1189

-16.7821

1.9767

Hour5

-5.0688

4.9660

-1.021

.3130

-15.0772

4.9396

Hour6

-5.4885

5.1964

-1.056

.2966

-15.9611

4.9841

Hour7

-7.2856

4.8986

-1.487

.1441

-17.1581

2.5870

Hour8

1.9288

4.5966

0.420

.6768

-7.3351

11.1927

Predicted values for: Sales

95% Confidence Interval

95% Prediction Interval

Temperature

Hour1

Hour2

Hour3

Hour4

Hour5

Hour6

Hour7

Hour8

Predicted

lower

upper

lower

upper

93

0

1

0

0

0

0

0

0

57.99273

51.22089

64.76457

40.79825

75.18721

Regression Analysis

0.212

Adjusted R²

0.050

n

54

R

0.460

k

9

Std. Error

7.842

Dep. Var.

Sales

ANOVA table

Source

SS

df

MS

F

p-value

Regression

726.2814

9  

80.6979

1.31

.2583

Residual

2,705.9709

44  

61.4993

Total

3,432.2523

53  

Regression output

confidence interval

variables

coefficients

std. error

   t (df=44)

p-value

95% lower

95% upper

Intercept

21.8336

31.7253

0.688

.4949

-42.1046

85.7718

Temperature

0.4498

0.3400

1.323

.1927

-0.2354

1.1350

Hour1

-5.2328

4.8986

-1.068

.2913

-15.1053

4.6398

Hour2

-5.6722

4.6290

-1.225

.2270

-15.0014

3.6569

Hour3

-6.2917

4.5291

-1.389

.1718

-15.4195

2.8360

Hour4

-7.4027

4.6539

-1.591

.1189

-16.7821

1.9767

Hour5

-5.0688

4.9660

-1.021

.3130

-15.0772

4.9396

Hour6

-5.4885

5.1964

-1.056

.2966

-15.9611

4.9841

Hour7

-7.2856

4.8986

-1.487

.1441

-17.1581

2.5870

Hour8

1.9288

4.5966

0.420

.6768

-7.3351

11.1927

Predicted values for: Sales

95% Confidence Interval

95% Prediction Interval

Temperature

Hour1

Hour2

Hour3

Hour4

Hour5

Hour6

Hour7

Hour8

Predicted

lower

upper

lower

upper

93

0

1

0

0

0

0

0

0

57.99273

51.22089

64.76457

40.79825

75.18721

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