Zagat’s publishes restaurant ratings for various locations in the United States. The following table contains the Zagat rating for food, décor, service, and the cost per person for a sample of 100 restaurants located in New York City and in a suburb of New York City. Develop a regression model to predict the cost per person, based on a variable that represents the sum of the ratings for food, décor, and service. Construct a scatter plot. For these data, b0 = - 46.7718 and b1 = 1.4963. Assuming a linear relationship, use the least- squares method to compute the regression coefficients b0 and b1. Interpret the meaning of the Y intercept, b0, and the slope, b1, in this problem. Location Food Décor Service Summated Rating Coded Location Cost Bins Midpoints City 22 14 19 55 0 33 19.99 25 City 20 15 20 55 0 26 29.99 35 City 23 19 21 63 0 43 39.99 45 City 19 18 18 55 0 32 49.99 55 City 24 16 18 58 0 44 59.99 65 City 22 22 21 65 0 44 69.99 75 City 22 20 20 62 0 50 79.99 85 City 20 19 19 58 0 42 89.99 City 21 17 19 57 0 44 City 20 18 18 56 0 36 City 23 22 24 69 0 61 City 20 19 20 59 0 50 City 21 19 21 61 0 51 City 24 19 21 64 0 50 City 25 23 23 71 0 76 City 22 21 21 64 0 53 City 23 15 22 60 0 44 City 26 22 24 72 0 77 City 21 23 21 65 0 57 City 24 15 19 58 0 43 City 21 15 19 55 0 29 City 23 16 16 55 0 34 City 25 21 26 72 0 77 City 22 20 21 63 0 50 City 26 25 24 75 0 74 City 23 21 21 65 0 56 City 22 19 17 58 0 67 City 26 20 23 69 0 57 City 26 23 25 74 0 66 City 24 23 24 71 0 80 City 22 23 23 68 0 68 City 24 16 23 63 0 42 City 20 17 19 56 0 48 City 25 19 23 67 0 60 City 23 20 21 64 0 35 City 21 19 22 62 0 45 City 20 16 18 54 0 32 City 23 15 18 56 0 25 City 26 24 24 74 0 74 City 21 18 18 57 0 43 City 22 16 19 57 0 39 City 19 23 21 63 0 55 City 24 19 21 64 0 65 City 23 16 20 59 0 35 City 24 26 22 72 0 61 City 21 17 18 56 0 37 City 21 17 19 57 0 54 City 23 19 22 64 0 41 City 23 19 21 63 0 33 City 23 14 19 56 0 27 Suburban 24 20 22 66 1 47 Suburban 22 18 22 62 1 48 Suburban 18 13 18 49 1 35 Suburban 22 23 20 65 1 59 Suburban 22 18 24 64 1 44 Suburban 23 25 24 72 1 51 Suburban 20 12 18 50 1 37 Suburban 19 18 19 56 1 36 Suburban 22 19 21 62 1 43 Suburban 27 21 27 75 1 52 Suburban 19 14 18 51 1 34 Suburban 22 11 19 52 1 38 Suburban 24 22 24 70 1 51 Suburban 19 15 19 53 1 34 Suburban 21 23 21 65 1 51 Suburban 21 19 21 61 1 34 Suburban 23 19 23 65 1 51 Suburban 23 20 22 65 1 56 Suburban 21 13 19 53 1 26 Suburban 24 19 22 65 1 34 Suburban 20 18 20 58 1 34 Suburban 24 22 24 70 1 44 Suburban 23 17 22 62 1 40 Suburban 23 16 21 60 1 31 Suburban 23 18 22 63 1 54 Suburban 19 12 22 53 1 41 Suburban 22 17 21 60 1 50 Suburban 26 27 24 77 1 71 Suburban 22 21 23 66 1 60 Suburban 19 15 17 51 1 37 Suburban 21 12 20 53 1 27 Suburban 26 18 22 66 1 34 Suburban 22 25 21 68 1 48 Suburban 21 21 21 63 1 39 Suburban 20 20 20 60 1 44 Suburban 22 18 22 62 1 41 Suburban 23 20 19 62 1 37 Suburban 24 21 23 68 1 47 Suburban 23 27 22 72 1 67 Suburban 24 24 22 70 1 68 Suburban 26 17 24 67 1 49 Suburban 22 22 19 63 1 29 Suburban 24 18 22 64 1 33 Suburban 20 19 20 59 1 39 Suburban 26 19 23 68 1 39 Suburban 22 15 21 58 1 28 Suburban 18 20 18 56 1 46 Suburban 26 27 25 78 1 70 Suburban 25 26 23 74 1 60 Suburban 22 25 22 69 1 52

Zagat’s publishes restaurant ratings for various locations in the United States. The following table contains the Zagat rating for food, décor, service, and the cost per person for a sample of 100 restaurants located in New York City and in a suburb of New York City. Develop a regression model to predict the cost per person, based on a variable that represents the sum of the ratings for food, décor, and service. Construct a scatter plot. For these data, b0 = - 46.7718 and b1 = 1.4963. Assuming a linear relationship, use the least- squares method to compute the regression coefficients b0 and b1. Interpret the meaning of the Y intercept, b0, and the slope, b1, in this problem. Location Food Décor Service Summated Rating Coded Location Cost Bins Midpoints City 22 14 19 55 0 33 19.99 25 City 20 15 20 55 0 26 29.99 35 City 23 19 21 63 0 43 39.99 45 City 19 18 18 55 0 32 49.99 55 City 24 16 18 58 0 44 59.99 65 City 22 22 21 65 0 44 69.99 75 City 22 20 20 62 0 50 79.99 85 City 20 19 19 58 0 42 89.99 City 21 17 19 57 0 44 City 20 18 18 56 0 36 City 23 22 24 69 0 61 City 20 19 20 59 0 50 City 21 19 21 61 0 51 City 24 19 21 64 0 50 City 25 23 23 71 0 76 City 22 21 21 64 0 53 City 23 15 22 60 0 44 City 26 22 24 72 0 77 City 21 23 21 65 0 57 City 24 15 19 58 0 43 City 21 15 19 55 0 29 City 23 16 16 55 0 34 City 25 21 26 72 0 77 City 22 20 21 63 0 50 City 26 25 24 75 0 74 City 23 21 21 65 0 56 City 22 19 17 58 0 67 City 26 20 23 69 0 57 City 26 23 25 74 0 66 City 24 23 24 71 0 80 City 22 23 23 68 0 68 City 24 16 23 63 0 42 City 20 17 19 56 0 48 City 25 19 23 67 0 60 City 23 20 21 64 0 35 City 21 19 22 62 0 45 City 20 16 18 54 0 32 City 23 15 18 56 0 25 City 26 24 24 74 0 74 City 21 18 18 57 0 43 City 22 16 19 57 0 39 City 19 23 21 63 0 55 City 24 19 21 64 0 65 City 23 16 20 59 0 35 City 24 26 22 72 0 61 City 21 17 18 56 0 37 City 21 17 19 57 0 54 City 23 19 22 64 0 41 City 23 19 21 63 0 33 City 23 14 19 56 0 27 Suburban 24 20 22 66 1 47 Suburban 22 18 22 62 1 48 Suburban 18 13 18 49 1 35 Suburban 22 23 20 65 1 59 Suburban 22 18 24 64 1 44 Suburban 23 25 24 72 1 51 Suburban 20 12 18 50 1 37 Suburban 19 18 19 56 1 36 Suburban 22 19 21 62 1 43 Suburban 27 21 27 75 1 52 Suburban 19 14 18 51 1 34 Suburban 22 11 19 52 1 38 Suburban 24 22 24 70 1 51 Suburban 19 15 19 53 1 34 Suburban 21 23 21 65 1 51 Suburban 21 19 21 61 1 34 Suburban 23 19 23 65 1 51 Suburban 23 20 22 65 1 56 Suburban 21 13 19 53 1 26 Suburban 24 19 22 65 1 34 Suburban 20 18 20 58 1 34 Suburban 24 22 24 70 1 44 Suburban 23 17 22 62 1 40 Suburban 23 16 21 60 1 31 Suburban 23 18 22 63 1 54 Suburban 19 12 22 53 1 41 Suburban 22 17 21 60 1 50 Suburban 26 27 24 77 1 71 Suburban 22 21 23 66 1 60 Suburban 19 15 17 51 1 37 Suburban 21 12 20 53 1 27 Suburban 26 18 22 66 1 34 Suburban 22 25 21 68 1 48 Suburban 21 21 21 63 1 39 Suburban 20 20 20 60 1 44 Suburban 22 18 22 62 1 41 Suburban 23 20 19 62 1 37 Suburban 24 21 23 68 1 47 Suburban 23 27 22 72 1 67 Suburban 24 24 22 70 1 68 Suburban 26 17 24 67 1 49 Suburban 22 22 19 63 1 29 Suburban 24 18 22 64 1 33 Suburban 20 19 20 59 1 39 Suburban 26 19 23 68 1 39 Suburban 22 15 21 58 1 28 Suburban 18 20 18 56 1 46 Suburban 26 27 25 78 1 70 Suburban 25 26 23 74 1 60 Suburban 22 25 22 69 1 52

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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Question

Construct a scatter plot. For these data, b0 = - 46.7718 and b1 = 1.4963.
Assuming a linear relationship, use the least- squares method to compute the regression coefficients b0 and b1.
Interpret the meaning of the Y intercept, b0, and the slope, b1, in this problem.

Location	Food	Décor	Service	Summated Rating	Coded Location	Cost	Bins	Midpoints
City	22	14	19	55	0	33	19.99	25
City	20	15	20	55	0	26	29.99	35
City	23	19	21	63	0	43	39.99	45
City	19	18	18	55	0	32	49.99	55
City	24	16	18	58	0	44	59.99	65
City	22	22	21	65	0	44	69.99	75
City	22	20	20	62	0	50	79.99	85
City	20	19	19	58	0	42	89.99
City	21	17	19	57	0	44
City	20	18	18	56	0	36
City	23	22	24	69	0	61
City	20	19	20	59	0	50
City	21	19	21	61	0	51
City	24	19	21	64	0	50
City	25	23	23	71	0	76
City	22	21	21	64	0	53
City	23	15	22	60	0	44
City	26	22	24	72	0	77
City	21	23	21	65	0	57
City	24	15	19	58	0	43
City	21	15	19	55	0	29
City	23	16	16	55	0	34
City	25	21	26	72	0	77
City	22	20	21	63	0	50
City	26	25	24	75	0	74
City	23	21	21	65	0	56
City	22	19	17	58	0	67
City	26	20	23	69	0	57
City	26	23	25	74	0	66
City	24	23	24	71	0	80
City	22	23	23	68	0	68
City	24	16	23	63	0	42
City	20	17	19	56	0	48
City	25	19	23	67	0	60
City	23	20	21	64	0	35
City	21	19	22	62	0	45
City	20	16	18	54	0	32
City	23	15	18	56	0	25
City	26	24	24	74	0	74
City	21	18	18	57	0	43
City	22	16	19	57	0	39
City	19	23	21	63	0	55
City	24	19	21	64	0	65
City	23	16	20	59	0	35
City	24	26	22	72	0	61
City	21	17	18	56	0	37
City	21	17	19	57	0	54
City	23	19	22	64	0	41
City	23	19	21	63	0	33
City	23	14	19	56	0	27
Suburban	24	20	22	66	1	47
Suburban	22	18	22	62	1	48
Suburban	18	13	18	49	1	35
Suburban	22	23	20	65	1	59
Suburban	22	18	24	64	1	44
Suburban	23	25	24	72	1	51
Suburban	20	12	18	50	1	37
Suburban	19	18	19	56	1	36
Suburban	22	19	21	62	1	43
Suburban	27	21	27	75	1	52
Suburban	19	14	18	51	1	34
Suburban	22	11	19	52	1	38
Suburban	24	22	24	70	1	51
Suburban	19	15	19	53	1	34
Suburban	21	23	21	65	1	51
Suburban	21	19	21	61	1	34
Suburban	23	19	23	65	1	51
Suburban	23	20	22	65	1	56
Suburban	21	13	19	53	1	26
Suburban	24	19	22	65	1	34
Suburban	20	18	20	58	1	34
Suburban	24	22	24	70	1	44
Suburban	23	17	22	62	1	40
Suburban	23	16	21	60	1	31
Suburban	23	18	22	63	1	54
Suburban	19	12	22	53	1	41
Suburban	22	17	21	60	1	50
Suburban	26	27	24	77	1	71
Suburban	22	21	23	66	1	60
Suburban	19	15	17	51	1	37
Suburban	21	12	20	53	1	27
Suburban	26	18	22	66	1	34
Suburban	22	25	21	68	1	48
Suburban	21	21	21	63	1	39
Suburban	20	20	20	60	1	44
Suburban	22	18	22	62	1	41
Suburban	23	20	19	62	1	37
Suburban	24	21	23	68	1	47
Suburban	23	27	22	72	1	67
Suburban	24	24	22	70	1	68
Suburban	26	17	24	67	1	49
Suburban	22	22	19	63	1	29
Suburban	24	18	22	64	1	33
Suburban	20	19	20	59	1	39
Suburban	26	19	23	68	1	39
Suburban	22	15	21	58	1	28
Suburban	18	20	18	56	1	46
Suburban	26	27	25	78	1	70
Suburban	25	26	23	74	1	60
Suburban	22	25	22	69	1	52

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