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Lab Insight: Apply the same steps in Lab 5.1 to the Alt Lab 5.1 Data.xlsx dataset.

Required:

Using regression analysis, determine the relationship between R&D expenditures and sales revenue.

Data: Alt Lab 5.1 Data.xlsx

Month	Date	R&D Expenditures	Revenues
1	1/1/16	2435469	20384212
2	2/1/16	2697876	20535593
3	3/1/16	2731559	20637044
4	4/1/16	2565438	20747676
5	5/1/16	1005592	21092832
6	6/1/16	3056330	21528540
7	7/1/16	2802698	22242734
8	8/1/16	3286307	22389131
9	9/1/16	3212612	22434133
10	10/1/16	1337317	21289511
11	11/1/16	1533246	20808222
12	12/1/16	1580733	23767423
13	1/1/17	1933609	22589738
14	2/1/17	2831031	20388249
15	3/1/17	2712264	24137112
16	4/1/17	2930931	21809162
17	5/1/17	1951727	25287839
18	6/1/17	1413536	21501027
19	7/1/17	1247415	21237285
20	8/1/17	1996692	21981449
21	9/1/17	2040628	23183174
22	10/1/17	2002760	26420315
23	11/1/17	1892409	21940383
24	12/1/17	2465441	25766458
25	1/1/18	1037135	22292534
26	2/1/18	2098594	24708767
27	3/1/18	3448216	25274538
28	4/1/18	2696272	28471841
29	5/1/18	1633558	25839737
30	6/1/18	980132	21351450
31	7/1/18	2390561	25380542
32	8/1/18	3135479	28730926
33	9/1/18	1526298	26248481
34	10/1/18	1565326	22629520
35	11/1/18	1300427	20301485
36	12/1/18	3267267	21964869
37	1/1/19	1775176	25083020
38	2/1/19	3619726	32693780
39	3/1/19	2805962	29229121
40	4/1/19	3523593	32646406
41	5/1/19	1591185	23437667
42	6/1/19	1101500	21991497
43	7/1/19	2118898	25535061
44	8/1/19	2109870	24100870
45	9/1/19	2952053	34223199
46	10/1/19	1924087	36840090
47	11/1/19	2881533	34933541
48	12/1/19	2676083	23031826
49	1/1/20	1367075	20197416
50	2/1/20	3398749	34693332
51	3/1/20	2304896	25493040
52	4/1/20	3384795	35241054
53	5/1/20	1963023	27458782
54	6/1/20	3320033	23251572
55	7/1/20	2857700	23355130
56	8/1/20	1773879	38766993
57	9/1/20	1087347	24045318
58	10/1/20	2270795	34496685
59	11/1/20	1904102	41777180
60	12/1/20	2071593	42037702
61	1/1/21	3441024	36845513
62	2/1/21	3075181	42982200
63	3/1/21	2141673	28907191
64	4/1/21	2655566	36120139
65	5/1/21	3791005	38842432
66	6/1/21	2578050	44902353
67	7/1/21	1874753	46020802
68	8/1/21	1600236	24505365
69	9/1/21	2026557	26772854
70	10/1/21	1672798	29893360
71	11/1/21	1781443	37749898
72	12/1/21	2962421	45839508
73	1/1/22	3793215	45771045
74	2/1/22	1667036	20959725
75	3/1/22	1830232	29547593
76	4/1/22	2722238	26110987
77	5/1/22	2781813	39471007
78	6/1/22	4077409	49643881
79	7/1/22	3855981	51488453
80	8/1/22	2232114	25815317
81	9/1/22	3446397	27302678
82	10/1/22	1800733	37451390
83	11/1/22	2756601	48353890
84	12/1/22	3195042	46657568
85	1/1/23	2760339	40633525
86	2/1/23	2338565	25392581
87	3/1/23	3644143	48646956
88	4/1/23	2449544	38849168
89	5/1/23	3330017	29996470
90	6/1/23	2566138	32110475
91	7/1/23	2966215	47316533
92	8/1/23	2587258	39050248
93	9/1/23	1990239	33411433
94	10/1/23	2776559	53439034
95	11/1/23	3574235	52850802
96	12/1/23	2967382	22663052
97	1/1/24	2466950	25082575
98	2/1/24	3401916	28084594
99	3/1/24	4151155	47809091
100	4/1/24	1297643	23546457
101	5/1/24	3848741	35702969
102	6/1/24	1661428	24737687
103	7/1/24	2463396	30445245
104	8/1/24	2634009	27588356
105	9/1/24	1212592	24275292
106	10/1/24	2817103	53954968
107	11/1/24	2033310	24642712
108	12/1/24	4074255	48239082

Analyze the Data: Refer to lab 5.1 in your text for additional instructions and steps.

Answer the following questions based on the details computed.

Note: Round adjusted R-squared value to 1 decimal place and revenue to 2 decimal places.