а) 50 53 90 54 35 41 s0 91 35 61 60 48 71 71 40 56 60 55 68 60 65 36 40 47 35 11 55 53 60 70 50 68 90 35 65 79 59 57 50 79 A data set consist of dependent variable (v) and independent variable (x) are shown above. It is claims that the relationship between the x and y can be modelled through a regression model as follows: j =a+bx where a and ò are the estimated values for a and ß (refer to Appendix). Determine the equation of the regression line to predict the y value from the x value. (ii) If the y value is 60, what is the value of x?
а) 50 53 90 54 35 41 s0 91 35 61 60 48 71 71 40 56 60 55 68 60 65 36 40 47 35 11 55 53 60 70 50 68 90 35 65 79 59 57 50 79 A data set consist of dependent variable (v) and independent variable (x) are shown above. It is claims that the relationship between the x and y can be modelled through a regression model as follows: j =a+bx where a and ò are the estimated values for a and ß (refer to Appendix). Determine the equation of the regression line to predict the y value from the x value. (ii) If the y value is 60, what is the value of x?
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
100%
I want the answer for (i) and (ii).
Please do not use excel.
![50
53
90
54
35
41
80
91
35
61
60
48
40
56
60
71
55
68
60
71
65
36
40
47
35
11
55
53
60
70
50
68
90
79
65
57
35
59
50
79
A data set consist of dependent variable (v) and independent variable (x) are shown
above. It is claims that the relationship between the x and y can be modelled through a
regression model as follows:
ŷ = a+bx
where a and b are the estimated values for a and B (refer to Appendix).
Determine the equation of the regression line to predict the y value from the x
value.
(11
If the y value is 60, what is the value of x?
(iii) Test the hypothesis that a=10 against the alternative a <10. Use a 0.05 level of
significance.
(iv)
Construct a 95% confidence interval for the average y with x=35.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F58c98c03-a205-4442-851c-5d58ade93297%2F5aacf09a-ddaf-46f4-9eab-1195cf9adb90%2F3937twb_processed.png&w=3840&q=75)
Transcribed Image Text:50
53
90
54
35
41
80
91
35
61
60
48
40
56
60
71
55
68
60
71
65
36
40
47
35
11
55
53
60
70
50
68
90
79
65
57
35
59
50
79
A data set consist of dependent variable (v) and independent variable (x) are shown
above. It is claims that the relationship between the x and y can be modelled through a
regression model as follows:
ŷ = a+bx
where a and b are the estimated values for a and B (refer to Appendix).
Determine the equation of the regression line to predict the y value from the x
value.
(11
If the y value is 60, what is the value of x?
(iii) Test the hypothesis that a=10 against the alternative a <10. Use a 0.05 level of
significance.
(iv)
Construct a 95% confidence interval for the average y with x=35.
![Appendix: QUESTION 4
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
0.45351335
0.20567436
0.16154515
Standard Error
16.174739
Observations
20
ANOVA
df
SS
MS
F
Significance F
Regression
1
1219.350728
1219.350728
4.66073144
0.044607262
Residual
18
4709.199272 261.6221818
Total
19
5928.55
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
32.50591447
12.63862114 2.571951015 0.019197049
5.953156759 59.05867218
0.471064604
0.21819934 2.158872724 0.044607262
0.012644801 0.929484407](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F58c98c03-a205-4442-851c-5d58ade93297%2F5aacf09a-ddaf-46f4-9eab-1195cf9adb90%2Fqvgu4z_processed.png&w=3840&q=75)
Transcribed Image Text:Appendix: QUESTION 4
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
0.45351335
0.20567436
0.16154515
Standard Error
16.174739
Observations
20
ANOVA
df
SS
MS
F
Significance F
Regression
1
1219.350728
1219.350728
4.66073144
0.044607262
Residual
18
4709.199272 261.6221818
Total
19
5928.55
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
32.50591447
12.63862114 2.571951015 0.019197049
5.953156759 59.05867218
0.471064604
0.21819934 2.158872724 0.044607262
0.012644801 0.929484407
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