Use the following data in any software like Excel or Eviews and develop a regression model using the price variable as the dependent variable. [you can copy and paste this in the software] Run and save your output results with a best-fit model with the highest significance. Copy your output results to a Word file and interpret your results. Results interpretation includes interpretation of the following: - Overall model significance - Coefficients (including their significance). Price Rooms Income In $ Tax Rate Commercial 100646 4.4 47150 1.3 24.84 100838 4.4 47150 1.46 24.84 92959 4 47735 2.94 25.18 93431 4 47735 3.08 24.77 106811 4.4 50990 2.48 7.89 108301 4.4 50990 2.97 9.01 114311 4.5 56195 3.6 25.35 114912 4.5 56195 3.77 25.52 109154 4.5 53915 2.21 13 110226 4.5 53915 2.13 13.24 97428 4.2 53345 2.19 9.16 102428 4.2 53345 2.05 9.1 96261 4.5 51470 3.91 16.04 96967 4.5 51470 3.97 15.46 118291 4.3 54080 1.54 13.19 118621 4.3 54080 1.92 13.3 95668 4.3 53270 1.03 21.3 98649 4.3 53270 0.97 21.84 100747 4.3 49895 3.32 24.95 101501 4.3 49895 3.36 24.94 104647 4.4 55880 2.66 18.64 105753 4.4 55880 2.71 19.04 105005 4.7 61805 1.87 9.96 106864 4.7 61805 1.6 10.3 101860 4.3 52625 1.94 26.67 102510 4.3 52625 2.42 28.43 106011 4.4 57620 2.37 19.75 106864 4.4 57620 2.37 20.79 97996 4.1 64625 2.46 13.92 98410 4.1 64625 2.53 14.12 109471 4.6 57455 2.24 22.53 110117 4.6 57455 2.22 24.51 110922 4.7 60140 2 12.89 111602 4.7 60140 2.2 13.39 110679 4.5 58835 2.5 18.73 111426 4.5 58835 2.63 18.42 99491 4.6 55610 2.7 13.72 100353 4.6 55610 2.56 13.58 92652 4.5 50120 2.73 20.44 92884 4.5 50120 2.53 20.94 101649 4.4 61010 3.88 14.37 103423 4.4 61010 3.82 13.77 111332 4.7 58205 2.89 8.38 113501 4.7 58205 2.81 9.3 109571 4.6 52835 1.85 12.99 112370 4.6 52835 1.63 12.18 100907 4.4 56510 3.59 22.37 101021 4.4 56510 3.31 22.74 124620 4.6 67895 2.22 28.2 125122 4.6 67895 2.35 28.37 113671 4.6 55910 2.8 14.12 114803 4.6 55910 3.01 15.82 99374 4.3 56825 1.96 16.45 100258 4.3 56825 2.24 16.35 94584 4.4 51785 2.2 19.03 95051 4.4 51785 2.24 19.27 94466 4.6 51275 4.41 18.91 97299 4.6 51275 4.17 18.52 103522 4.2 51320 3.4 14.37 106451 4.2 51320 3.85 16.69 105113 4.6 54155 3.41 17.25 105898 4.6 54155 3.41 18.83 117074 5 52970 2.51 9.92 119141 5 52970 2.72 9.84 92316 4.3 54140 4.7 9.55 91599 4.3 54140 5.34 9.46 100360 4.3 58760 4.16 19.5 100414 4.3 58760 4.16 19.83 104375 4.3 61640 3.78 7.64 105453 4.3 61640 4.28 24.93 114465 4.4 54935 0.7 14.21 118744 4.4 54935 0.89 13.08 107574 4.4 50615 2.91 18.36 107832 4.4 50615 2.98 16.95 136952 4.7 60140 2.35 11.21 136472 4.7 60140 2.15 11.57 99331 4.4 46085 4.02 25.01 99941 4.4 46085 3.95 27.56 105150 4.8 60305 3.49 11.77 108168 4.8 60305 3.5 11.45 121064 4.5 54245 1.58 3.94 122638 4.5 54245 1.94 5.72 114224 4.1 51500 1.84 3.26 115775 4.1 51500 2.25 2.8 112955 5.1 64175 2.9 8.86 115457 5.1 64175 2.98 7.62 132758 5.2 60680 1.47 9.48 131871 5.2 60680 1.91 9.63 102710 4.4 52955 2.31 17.07 103014 4.4 52955 2.97 16.86

Use the following data in any software like Excel or Eviews and develop a regression model using the price variable as the dependent variable. [you can copy and paste this in the software] Run and save your output results with a best-fit model with the highest significance. Copy your output results to a Word file and interpret your results. Results interpretation includes interpretation of the following: - Overall model significance - Coefficients (including their significance). Price Rooms Income In $ Tax Rate Commercial 100646 4.4 47150 1.3 24.84 100838 4.4 47150 1.46 24.84 92959 4 47735 2.94 25.18 93431 4 47735 3.08 24.77 106811 4.4 50990 2.48 7.89 108301 4.4 50990 2.97 9.01 114311 4.5 56195 3.6 25.35 114912 4.5 56195 3.77 25.52 109154 4.5 53915 2.21 13 110226 4.5 53915 2.13 13.24 97428 4.2 53345 2.19 9.16 102428 4.2 53345 2.05 9.1 96261 4.5 51470 3.91 16.04 96967 4.5 51470 3.97 15.46 118291 4.3 54080 1.54 13.19 118621 4.3 54080 1.92 13.3 95668 4.3 53270 1.03 21.3 98649 4.3 53270 0.97 21.84 100747 4.3 49895 3.32 24.95 101501 4.3 49895 3.36 24.94 104647 4.4 55880 2.66 18.64 105753 4.4 55880 2.71 19.04 105005 4.7 61805 1.87 9.96 106864 4.7 61805 1.6 10.3 101860 4.3 52625 1.94 26.67 102510 4.3 52625 2.42 28.43 106011 4.4 57620 2.37 19.75 106864 4.4 57620 2.37 20.79 97996 4.1 64625 2.46 13.92 98410 4.1 64625 2.53 14.12 109471 4.6 57455 2.24 22.53 110117 4.6 57455 2.22 24.51 110922 4.7 60140 2 12.89 111602 4.7 60140 2.2 13.39 110679 4.5 58835 2.5 18.73 111426 4.5 58835 2.63 18.42 99491 4.6 55610 2.7 13.72 100353 4.6 55610 2.56 13.58 92652 4.5 50120 2.73 20.44 92884 4.5 50120 2.53 20.94 101649 4.4 61010 3.88 14.37 103423 4.4 61010 3.82 13.77 111332 4.7 58205 2.89 8.38 113501 4.7 58205 2.81 9.3 109571 4.6 52835 1.85 12.99 112370 4.6 52835 1.63 12.18 100907 4.4 56510 3.59 22.37 101021 4.4 56510 3.31 22.74 124620 4.6 67895 2.22 28.2 125122 4.6 67895 2.35 28.37 113671 4.6 55910 2.8 14.12 114803 4.6 55910 3.01 15.82 99374 4.3 56825 1.96 16.45 100258 4.3 56825 2.24 16.35 94584 4.4 51785 2.2 19.03 95051 4.4 51785 2.24 19.27 94466 4.6 51275 4.41 18.91 97299 4.6 51275 4.17 18.52 103522 4.2 51320 3.4 14.37 106451 4.2 51320 3.85 16.69 105113 4.6 54155 3.41 17.25 105898 4.6 54155 3.41 18.83 117074 5 52970 2.51 9.92 119141 5 52970 2.72 9.84 92316 4.3 54140 4.7 9.55 91599 4.3 54140 5.34 9.46 100360 4.3 58760 4.16 19.5 100414 4.3 58760 4.16 19.83 104375 4.3 61640 3.78 7.64 105453 4.3 61640 4.28 24.93 114465 4.4 54935 0.7 14.21 118744 4.4 54935 0.89 13.08 107574 4.4 50615 2.91 18.36 107832 4.4 50615 2.98 16.95 136952 4.7 60140 2.35 11.21 136472 4.7 60140 2.15 11.57 99331 4.4 46085 4.02 25.01 99941 4.4 46085 3.95 27.56 105150 4.8 60305 3.49 11.77 108168 4.8 60305 3.5 11.45 121064 4.5 54245 1.58 3.94 122638 4.5 54245 1.94 5.72 114224 4.1 51500 1.84 3.26 115775 4.1 51500 2.25 2.8 112955 5.1 64175 2.9 8.86 115457 5.1 64175 2.98 7.62 132758 5.2 60680 1.47 9.48 131871 5.2 60680 1.91 9.63 102710 4.4 52955 2.31 17.07 103014 4.4 52955 2.97 16.86

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Related questions

Concept explainers

Question

Use the following data in any software like Excel or Eviews and develop a regression model using the price variable as the dependent variable. [you can copy and paste this in the software]

Run and save your output results with a best-fit model with the highest significance.

Copy your output results to a Word file and interpret your results.

Results interpretation includes interpretation of the following:

- Overall model significance

- Coefficients (including their significance).

Price	Rooms	Income In $	Tax Rate	Commercial
100646	4.4	47150	1.3	24.84
100838	4.4	47150	1.46	24.84
92959	4	47735	2.94	25.18
93431	4	47735	3.08	24.77
106811	4.4	50990	2.48	7.89
108301	4.4	50990	2.97	9.01
114311	4.5	56195	3.6	25.35
114912	4.5	56195	3.77	25.52
109154	4.5	53915	2.21	13
110226	4.5	53915	2.13	13.24
97428	4.2	53345	2.19	9.16
102428	4.2	53345	2.05	9.1
96261	4.5	51470	3.91	16.04
96967	4.5	51470	3.97	15.46
118291	4.3	54080	1.54	13.19
118621	4.3	54080	1.92	13.3
95668	4.3	53270	1.03	21.3
98649	4.3	53270	0.97	21.84
100747	4.3	49895	3.32	24.95
101501	4.3	49895	3.36	24.94
104647	4.4	55880	2.66	18.64
105753	4.4	55880	2.71	19.04
105005	4.7	61805	1.87	9.96
106864	4.7	61805	1.6	10.3
101860	4.3	52625	1.94	26.67
102510	4.3	52625	2.42	28.43
106011	4.4	57620	2.37	19.75
106864	4.4	57620	2.37	20.79
97996	4.1	64625	2.46	13.92
98410	4.1	64625	2.53	14.12
109471	4.6	57455	2.24	22.53
110117	4.6	57455	2.22	24.51
110922	4.7	60140	2	12.89
111602	4.7	60140	2.2	13.39
110679	4.5	58835	2.5	18.73
111426	4.5	58835	2.63	18.42
99491	4.6	55610	2.7	13.72
100353	4.6	55610	2.56	13.58
92652	4.5	50120	2.73	20.44
92884	4.5	50120	2.53	20.94
101649	4.4	61010	3.88	14.37
103423	4.4	61010	3.82	13.77
111332	4.7	58205	2.89	8.38
113501	4.7	58205	2.81	9.3
109571	4.6	52835	1.85	12.99
112370	4.6	52835	1.63	12.18
100907	4.4	56510	3.59	22.37
101021	4.4	56510	3.31	22.74
124620	4.6	67895	2.22	28.2
125122	4.6	67895	2.35	28.37
113671	4.6	55910	2.8	14.12
114803	4.6	55910	3.01	15.82
99374	4.3	56825	1.96	16.45
100258	4.3	56825	2.24	16.35
94584	4.4	51785	2.2	19.03
95051	4.4	51785	2.24	19.27
94466	4.6	51275	4.41	18.91
97299	4.6	51275	4.17	18.52
103522	4.2	51320	3.4	14.37
106451	4.2	51320	3.85	16.69
105113	4.6	54155	3.41	17.25
105898	4.6	54155	3.41	18.83
117074	5	52970	2.51	9.92
119141	5	52970	2.72	9.84
92316	4.3	54140	4.7	9.55
91599	4.3	54140	5.34	9.46
100360	4.3	58760	4.16	19.5
100414	4.3	58760	4.16	19.83
104375	4.3	61640	3.78	7.64
105453	4.3	61640	4.28	24.93
114465	4.4	54935	0.7	14.21
118744	4.4	54935	0.89	13.08
107574	4.4	50615	2.91	18.36
107832	4.4	50615	2.98	16.95
136952	4.7	60140	2.35	11.21
136472	4.7	60140	2.15	11.57
99331	4.4	46085	4.02	25.01
99941	4.4	46085	3.95	27.56
105150	4.8	60305	3.49	11.77
108168	4.8	60305	3.5	11.45
121064	4.5	54245	1.58	3.94
122638	4.5	54245	1.94	5.72
114224	4.1	51500	1.84	3.26
115775	4.1	51500	2.25	2.8
112955	5.1	64175	2.9	8.86
115457	5.1	64175	2.98	7.62
132758	5.2	60680	1.47	9.48
131871	5.2	60680	1.91	9.63
102710	4.4	52955	2.31	17.07
103014	4.4	52955	2.97	16.86

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