Being able to predict the daily demand of sandwiches would reduce the amount of discarded food at the end of the day. You and your team created a theory that high volume days would begin busy and low volume days would begin slow. Since 12 p.m. is your highest volume hour, you decided to compare the 12 p.m. volume with the daily volume to test your theory.

You pulled historical data showing the 12 p.m. volume and the total daily volume.

Please use theRegression Analysis DataUse Excel to run a regression analysis and answer the following questions.

Date	12 p.m. Sales	Daily Sales
1-May	130	587
2-May	124	568
3-May	112	507
4-May	130	588
5-May	137	621
6-May	112	501
7-May	141	640
8-May	123	558
9-May	121	544
10-May	112	499
11-May	139	635
12-May	131	591
13-May	134	610
14-May	149	677
15-May	133	606
16-May	115	531
17-May	148	671
18-May	129	597
19-May	155	714
20-May	131	596
21-May	125	567
22-May	125	563
23-May	119	532
24-May	143	649
25-May	132	597
26-May	120	550
27-May	141	633
28-May	114	519
29-May	119	539
30-May	138	628
31-May	147	674
1-Jun	129	591
2-Jun	132	600
3-Jun	150	679
4-Jun	134	616
5-Jun	139	630
6-Jun	105	484
7-Jun	135	609
8-Jun	148	682
9-Jun	124	558

1. What is the R-squared of the Regression Analysis?

2. What is your predicted daily volume if you only have 90 sales at the 12 p.m. hour?