An engineering student wants to study the impact of temperature and humidity on yield. The following data was recorded by the student. S.N Temperature Humidity 40 Yield 1 57 112 2 45 54 118 3 50 54 128 4 55 60 121 60 66 126 65 59 136 7 70 61 144 8 75 58 142 9 80 59 149 10 85 56 165 A: Simple Linear regression model between yield and temperature. f) Estimate the yield when the temperature is 35F. g) Find the predicted value for each y using the temperature value and the equation obtained in part b. h) Find the residual value. 5. 6.
An engineering student wants to study the impact of temperature and humidity on yield. The following data was recorded by the student. S.N Temperature Humidity 40 Yield 1 57 112 2 45 54 118 3 50 54 128 4 55 60 121 60 66 126 65 59 136 7 70 61 144 8 75 58 142 9 80 59 149 10 85 56 165 A: Simple Linear regression model between yield and temperature. f) Estimate the yield when the temperature is 35F. g) Find the predicted value for each y using the temperature value and the equation obtained in part b. h) Find the residual value. 5. 6.
Chapter3: Polynomial Functions
Section: Chapter Questions
Problem 18T
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![An engineering student wants to study the impact of temperature and humidity on yield.
The following data was recorded by the student.
S.N Temperature Humidity
Yield
1
40
57
112
45
54
118
50
54
128
4
55
60
121
5
60
66
126
65
59
136
7
70
61
144
8
75
58
142
9
80
59
149
10
85
56
165
A: Simple Linear regression model between yield and temperature.
f) Estimate the yield when the temperature is 35F.
g) Find the predicted value for each y using the temperature value and the equation
obtained in part b.
h) Find the residual value.
i) Using Rstudio, check the assumption of the model obtained in part b.
2.
3.
6.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fddddbe93-8842-4854-8b25-33cd2589bbfe%2F47d0ea72-bc83-46a5-94a4-796895a6e923%2Fg3szzwr_processed.png&w=3840&q=75)
Transcribed Image Text:An engineering student wants to study the impact of temperature and humidity on yield.
The following data was recorded by the student.
S.N Temperature Humidity
Yield
1
40
57
112
45
54
118
50
54
128
4
55
60
121
5
60
66
126
65
59
136
7
70
61
144
8
75
58
142
9
80
59
149
10
85
56
165
A: Simple Linear regression model between yield and temperature.
f) Estimate the yield when the temperature is 35F.
g) Find the predicted value for each y using the temperature value and the equation
obtained in part b.
h) Find the residual value.
i) Using Rstudio, check the assumption of the model obtained in part b.
2.
3.
6.
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