A grocery store designed to handle a maximum of one thousand customers per day has noticed an increase in popularity. It believes that the store will soon reach its maximum capacity but it wants to be certain. The store decided to look at its daily attendance for the past 300 days, and to develop a forecasting model to predict when it would reach capacity. Develop a forecast model using the data in file BA3653A3Q1.xlsx, found in D2L. Do not use the naive method. Should one model be used to model the entire data set? Consider if all the data should be used in creating your prediction. Answer the following questions: a. Using your model, predict how many days in the future it will take for the store to reach maximum capacity. b. Suppose an expansion can be made to increase capacity to 1500 customers/day. If the popularity increase continues, estimate how much more time (in days) it will take for the store to reach its new capacity after expansion. c. A manager is convinced that the naive method is the best at predicting customer usage. Show (using numbers) that your method is superior at creating forecasts. d. Another manager is concerned that there is too much random variation in the number of customers to be able to discern any pattern. Quantify the strength of the relationship to determine if there is too much random variation.

day	usage
1	495
2	502
3	499
4	498
5	499
6	502
7	489
8	502
9	497
10	504
11	509
12	492
13	501
14	499
15	501
16	507
17	500
18	502
19	499
20	502
21	499
22	505
23	504
24	507
25	505
26	502
27	502
28	500
29	505
30	501
31	503
32	493
33	501
34	501
35	489
36	493
37	499
38	502
39	499
40	513
41	498
42	505
43	501
44	506
45	500
46	499
47	496
48	490
49	498
50	497
51	500
52	499
53	492
54	504
55	503
56	504
57	496
58	505
59	502
60	498
61	504
62	501
63	503
64	500
65	503
66	503
67	508
68	496
69	499
70	506
71	502
72	498
73	498
74	500
75	503
76	502
77	497
78	502
79	503
80	503
81	495
82	504
83	497
84	507
85	502
86	502
87	504
88	502
89	501
90	496
91	505
92	505
93	495
94	494
95	496
96	505
97	495
98	495
99	497
100	503
101	497
102	500
103	503
104	507
105	501
106	501
107	502
108	507
109	510
110	509
111	509
112	508
113	517
114	524
115	515
116	519
117	516
118	516
119	514
120	514
121	522
122	520
123	524
124	519
125	522
126	528
127	523
128	528
129	528
130	530
131	528
132	531
133	530
134	530
135	534
136	537
137	535
138	542
139	544
140	546
141	542
142	529
143	548
144	545
145	537
146	546
147	543
148	553
149	555
150	549
151	554
152	548
153	554
154	552
155	552
156	559
157	558
158	556
159	560
160	565
161	562
162	554
163	562
164	562
165	563
166	568
167	562
168	571
169	572
170	566
171	573
172	569
173	580
174	569
175	571
176	579
177	575
178	576
179	579
180	584
181	580
182	583
183	581
184	580
185	583
186	585
187	591
188	592
189	585
190	587
191	598
192	595
193	596
194	590
195	599
196	597
197	594
198	604
199	607
200	602
201	602
202	597
203	601
204	602
205	608
206	606
207	606
208	606
209	611
210	608
211	615
212	611
213	615
214	613
215	614
216	610
217	618
218	617
219	623
220	625
221	625
222	622
223	619
224	629
225	618
226	620
227	630
228	629
229	630
230	630
231	636
232	634
233	630
234	633
235	633
236	629
237	638
238	639
239	635
240	648
241	643
242	642
243	636
244	647
245	643
246	647
247	645
248	644
249	652
250	651
251	653
252	648
253	647
254	650
255	651
256	659
257	652
258	661
259	663
260	668
261	656
262	660
263	664
264	664
265	670
266	667
267	674
268	676
269	672
270	673
271	668
272	672
273	674
274	672
275	670
276	673
277	668
278	681
279	674
280	682
281	683
282	686
283	681
284	685
285	688
286	679
287	685
288	686
289	684
290	688
291	690
292	689
293	698
294	693
295	692
296	697
297	691
298	700
299	697
300	702