In: Statistics and Probability
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 |
The regression output is as follows
I have taken all the 100 values in the Excel, though only some are visible in the image
Question (1)
The regression equation is
Predicted Customer = 102.0435 + 0 * Morning + 20.1918 * Afternoon + (-37.7622) * Evening + 1.9208 * Night
Question (2)
predicted number of customers during the morning shifts will be obtained by keeping Morning variable as 1 and rest all othe vairables as 0.
So predicted number of customers during the morning shift = 102.0435 + 0 * 1 + 20.1918 * 0 + (-37.7622) * 0 + 1.9208 * 0
So predicted number of customers during the morning shift = 102.0435
= 103 rounded to next hearest integer
Question (3)
predicted number of customers during the aftternoon shifts will be obtained by keeping Afternoon variable as 1 and rest all othe vairables as 0.
So predicted number of customers during the Afternoon shift = 102.0435 + 0 * 0 + 20.1918 * 1 + (-37.7622) * 0 + 1.9208 * 0
So predicted number of customers during the morning shift = 102.0435 + 20.1918
= 122.2353
= 123 rounded to next highest integer