10.3.6 The following data were collected on a simple random sample of 20 patients with hypertension. The variables are Y mean arterial blood pressure(mm Hg) X₁ = age(years) X2 = weight(kg) X3 = body surface area(sq m) = Xs X6 X4 duration of hypertension (years) basal pulse (beatsthn/min) measure of stress Patient Y X₁ X2 X3 X4 X5 X6 1 105 47 85.4 1.75 5.1 63 33 2 115 49 94.2 2.10 3.8 70 14 3 116 49 95.3 1.98 8.2 72 10 4 117 50 94.7 2.01 5.8 73 99 5 112 51 89.4 1.89 7.0 72 95 6 121 48 99.5 2.25 9.3 71 10 7 121 49 99.8 2.25 2.5 69 42 8 110 47 90.9 1.90 6.2 66 8 9 110 49 89.2 1.83 7.1 69 62 10 114 48 92.7 2.07 5.6 64 35 11 114 47 94.4 2.07 5.3 74 90 12 115 49 94.1 1.98 5.6 71 21 13 114 50 91.6 2.05 10.2 68 47 14 106 45 87.1 1.92 5.6 67 80 15 125 52 101.3 2.19 10.0 76 98 16 114 46 94.5 1.98 7.4 69 95 17 106 46 87.0 1.87 3.6 62 18 18 113 46 94.5 1.90 4.3 70 12 19 110 48 90.5 1.88 9.0 71 99 20 122 56 95.7 2.09 7.0 75 99 Homework from Chapter 10. Consider the data for Q 10.3.6 of the book. Question 1. (a) Draw scatter plots of Y against each of the six variables X1, ..., X6 and do a simple linear regression of Y on each of those variables. Comment on the results. (b) Perform the Analysis of Variance (ANOVA) for the multiple regression model. (c) Test significance of each of the regression parameters ẞ₁......ẞ6 using significance level a 0.05. State the p-value in each case. (d) Construct a 95% C. I. for each parameter found significant in (b). (e) Using the residuals test normality assumption about the errors. Question 2. Now consider the data set consisting of values of Y and the variables for which the Bi's were found significant in Question 1. (a) Perform ANOVA for the multiple regression model. (b) Compute the coefficient of multiple determination. (c) Compute the simple correlation coefficient between all pairs of variables (d) Compute the partial correlation coefficient between Y and each of the other variables. Question 3. Suppose you are now told to choose, for the data in Question 2, the best multiple regression model containing only two independent variables. What would be the model? (Use coefficient of multiple determination to make your decision). ||

10.3.6 The following data were collected on a simple random sample of 20 patients with hypertension. The variables are Y mean arterial blood pressure(mm Hg) X₁ = age(years) X2 = weight(kg) X3 = body surface area(sq m) = Xs X6 X4 duration of hypertension (years) basal pulse (beatsthn/min) measure of stress Patient Y X₁ X2 X3 X4 X5 X6 1 105 47 85.4 1.75 5.1 63 33 2 115 49 94.2 2.10 3.8 70 14 3 116 49 95.3 1.98 8.2 72 10 4 117 50 94.7 2.01 5.8 73 99 5 112 51 89.4 1.89 7.0 72 95 6 121 48 99.5 2.25 9.3 71 10 7 121 49 99.8 2.25 2.5 69 42 8 110 47 90.9 1.90 6.2 66 8 9 110 49 89.2 1.83 7.1 69 62 10 114 48 92.7 2.07 5.6 64 35 11 114 47 94.4 2.07 5.3 74 90 12 115 49 94.1 1.98 5.6 71 21 13 114 50 91.6 2.05 10.2 68 47 14 106 45 87.1 1.92 5.6 67 80 15 125 52 101.3 2.19 10.0 76 98 16 114 46 94.5 1.98 7.4 69 95 17 106 46 87.0 1.87 3.6 62 18 18 113 46 94.5 1.90 4.3 70 12 19 110 48 90.5 1.88 9.0 71 99 20 122 56 95.7 2.09 7.0 75 99 Homework from Chapter 10. Consider the data for Q 10.3.6 of the book. Question 1. (a) Draw scatter plots of Y against each of the six variables X1, ..., X6 and do a simple linear regression of Y on each of those variables. Comment on the results. (b) Perform the Analysis of Variance (ANOVA) for the multiple regression model. (c) Test significance of each of the regression parameters ẞ₁......ẞ6 using significance level a 0.05. State the p-value in each case. (d) Construct a 95% C. I. for each parameter found significant in (b). (e) Using the residuals test normality assumption about the errors. Question 2. Now consider the data set consisting of values of Y and the variables for which the Bi's were found significant in Question 1. (a) Perform ANOVA for the multiple regression model. (b) Compute the coefficient of multiple determination. (c) Compute the simple correlation coefficient between all pairs of variables (d) Compute the partial correlation coefficient between Y and each of the other variables. Question 3. Suppose you are now told to choose, for the data in Question 2, the best multiple regression model containing only two independent variables. What would be the model? (Use coefficient of multiple determination to make your decision). ||

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

Question

please i want full answer for all question 1 and 2 and 3 using minitab or excel asp pllease
Homework from Chapter 10. Consider the data for Q 10.3.6 of the book. Question 1.
(a) Draw scatter plots of Y against each of the six variables X1, ...., X6 and do a simple linear regression of Y on each of those variables. Comment on the results.
(b) Perform the Analysis of Variance (ANOVA) for the multiple regression model.
(c) Test significance of each of the regression parameters 1, ...., B6 using significance level a =
0.05. State the p-value in each case.
(d) Construct a 95% C. I. for each parameter found significant in (b). (e) Using the residuals test normality assumption about the errors.
Question 2. Now consider the data set consisting of values of Y and the variables for which the Bi's were found significant in Question 1.
(a) Perform ANOVA for the multiple regression model.
(b) Compute the coefficient of multiple determination.
(c) Compute the simple correlation coefficient between all pairs of variables
(d) Compute the partial correlation coefficient between Y and each of the other variables.
Question 3. Suppose you are now told to choose, for the data in Question 2, the best multiple regression model containing only two independent variables. What would be the model? (Use coefficient of multiple determination to make your decision).

10.3.6 The following data were collected on a simple random sample of 20 patients with hypertension. The
variables are
Y
mean arterial blood pressure(mm Hg)
X₁ = age(years)
X2 = weight(kg)
X3
=
body surface area(sq m)
=
Xs
X6
X4 duration of hypertension (years)
basal pulse (beatsthn/min)
measure of stress
Patient
Y
X₁
X2
X3
X4
X5
X6
1
105
47
85.4
1.75
5.1
63
33
2
115
49
94.2
2.10
3.8
70
14
3
116
49
95.3
1.98
8.2
72
10
4
117
50
94.7
2.01
5.8
73
99
5
112
51
89.4
1.89
7.0
72
95
6
121
48
99.5
2.25
9.3
71
10
7
121
49
99.8
2.25
2.5
69
42
8
110
47
90.9
1.90
6.2
66
8
9
110
49
89.2
1.83
7.1
69
62
10
114
48
92.7
2.07
5.6
64
35
11
114
47
94.4
2.07
5.3
74
90
12
115
49
94.1
1.98
5.6
71
21
13
114
50
91.6
2.05
10.2
68
47
14
106
45
87.1
1.92
5.6
67
80
15
125
52
101.3
2.19
10.0
76
98
16
114
46
94.5
1.98
7.4
69
95
17
106
46
87.0
1.87
3.6
62
18
18
113
46
94.5
1.90
4.3
70
12
19
110
48
90.5
1.88
9.0
71
99
20
122
56
95.7
2.09
7.0
75
99
Homework from Chapter 10. Consider the data for Q 10.3.6 of the book. Question 1.
(a) Draw scatter plots of Y against each of the six variables X1, ..., X6 and do a simple linear
regression of Y on each of those variables. Comment on the results.
(b) Perform the Analysis of Variance (ANOVA) for the multiple regression model.
(c) Test significance of each of the regression parameters ẞ₁......ẞ6 using significance level a
0.05. State the p-value in each case.
(d) Construct a 95% C. I. for each parameter found significant in (b). (e) Using the residuals test
normality assumption about the errors.
Question 2. Now consider the data set consisting of values of Y and the variables for which the
Bi's were found significant in Question 1.
(a) Perform ANOVA for the multiple regression model.
(b) Compute the coefficient of multiple determination.
(c) Compute the simple correlation coefficient between all pairs of variables
(d) Compute the partial correlation coefficient between Y and each of the other variables.
Question 3. Suppose you are now told to choose, for the data in Question 2, the best multiple
regression model containing only two independent variables. What would be the model? (Use
coefficient of multiple determination to make your decision). ||

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