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8. The manager of a diner wants to re-evaluate his staffing needs depending on variations in customer traffic during the day. He collects data on the number of customers served along with four dummy v...

8. The manager of a diner wants to re-evaluate his staffing needs depending on variations in customer traffic during the day. He collects data on the number of customers served along with four dummy variables representing the morning, afternoon, evening, and night shifts. The dummy variable Morning equals 1 if the information was from the morning shift and 0 otherwise. The dummy variable Afternoon equals 1 if the information was from the afternoon shift and 0 otherwise. The dummy variable Evening equals 1 if the information was from the evening shift and 0 otherwise. The dummy variable Night equals 1 if the information was from the night shift and 0 otherwise. Data is posted on Webcampus in excel file titled Shifts Data.

Estimate a regression model using the number of customers as the response (dependent) variable and the shift dummy variables as the explanatory (independent) variables.

  1. What is the regression equation? Attach the Excel output.
  1. What is the predicted number of customers during the morning shifts?
  1. What is the predicted number of customers during the afternoon shifts?
  1. What is the predicted number of customers during the evening shifts?
  1. What is the predicted number of customers during the night shifts?
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Answer #1

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ANSWER:

EXPLANATION:

data taken

Customers Morning Afternoon Evening Night
99 0 0 0 1
148 0 1 0 0
130 0 1 0 0
106 0 0 0 1
133 0 0 0 1
119 0 0 0 1
105 1 0 0 0
74 1 0 0 0
106 0 0 0 1
94 0 1 0 0
69 0 0 1 0
86 0 0 1 0
95 1 0 0 0
99 0 1 0 0
71 0 0 1 0
80 0 0 1 0
63 0 0 1 0
93 0 0 0 1
117 1 0 0 0
136 0 1 0 0
91 0 0 1 0
131 0 0 0 1
112 0 1 0 0
88 1 0 0 0
59 0 0 1 0
44 0 0 1 0
129 0 0 0 1
82 0 0 1 0
78 0 0 0 1
109 1 0 0 0
51 0 0 1 0
71 1 0 0 0
57 0 0 1 0
112 0 1 0 0
61 0 0 1 0
83 0 1 0 0
101 1 0 0 0
92 0 0 0 1
48 0 0 1 0
73 0 0 1 0
83 0 0 0 1
133 0 1 0 0
69 0 0 1 0
135 1 0 0 0
135 0 1 0 0
96 1 0 0 0
50 0 0 1 0
110 0 0 0 1
58 0 0 1 0
121 0 1 0 0
113 1 0 0 0
65 0 0 0 1
45 0 0 1 0
41 0 0 1 0
86 0 0 1 0
110 0 0 0 1
70 0 0 1 0
104 1 0 0 0
121 0 0 0 1
79 1 0 0 0
121 0 0 0 1
89 0 0 0 1
126 0 1 0 0
75 0 0 1 0
67 0 0 1 0
100 0 0 0 1
93 0 0 0 1
56 0 0 1 0
91 0 0 0 1
129 0 1 0 0
96 0 0 1 0
78 0 0 0 1
48 0 0 1 0
69 0 0 1 0
156 0 1 0 0
98 0 0 0 1
90 0 0 0 1
133 0 0 0 1
93 1 0 0 0
130 0 0 0 1
112 1 0 0 0
109 0 0 0 1
86 0 0 1 0
52 0 0 1 0
104 1 0 0 0
27 0 0 1 0
119 1 0 0 0
113 1 0 0 0
123 0 1 0 0
95 1 0 0 0
93 1 0 0 0
130 0 1 0 0
102 1 0 0 0
111 1 0 0 0
103 0 0 0 1
69 0 0 1 0
101 0 0 0 1
118 1 0 0 0
58 0 0 1 0
111 0 1 0 0

(a) Regression Statistics

Multiple R = 0.789459

R Square = 0.623245

Adjusted R Square = 0.601055

Standard Error = 17.03472

Observations = 100

ANOVA

df SS MS F Significance F
Regression 4        46083.06 11520.77 52.93586 2.23E-23
Residual 96        27857.45
     290.1818
Total 100
       73940.51
Coefficients Standard error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 102.0435 3.551985 28.72858 6.17E-49 94.99284 109.0941 94.99284 109.0941
Morning 0 0 65535 #NUM! 0 0 0 0
Afternoon 20.19182 5.448496 3.705943 #NUM! 9.376636 31.007 9.376636 31.007
Evening -37.7622 4.656692 -8.10924 1.67E-12 -47.0057 -28.5188 -47.0057 -28.5188
Night 1.920807 4.79377 0.400688 0.68954 -7.59475 11.43637 -7.59475 11.43637

Customers = 102.0435 + 20.19*Afternoon-37.7622*Evening+1.921*Night

(b)

In morning shift,

Customers = 102.0435 + 20.19*0-37.7622*0+1.921*0

Hence, the predicted number of customers = 102.0435

(c)

In afternoon

Customers = 102.0435 + 20.19*1-37.7622*0+1.921*0

Hence, the predicted number of customers = 122.23

(d)

In evenings

Customers = 102.0435 + 20.19*0-37.7622*1+1.921*0

Hence, the predicted number of customers = 64.28

(e)

In night shifts,

Customers = 102.0435 + 20.19*0-37.7622*0+1.921*1

Hence, the predicted number of customers = 103.9645

HOPE IT HELPS YOU

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THANKS GOODLUCK

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