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 40 57 112 45 54 118 3 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. a) Compute the correlation coefficient between yield and temperature. b) Find the equation of regression line between yields on temperature using least square method. c) Draw the şcatter diagram between yield and temperature.

A First Course in Probability (10th Edition)
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Publisher:Sheldon Ross
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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
40
57
112
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.
a) Compute the correlation coefficient between yield and temperature.
b) Find the equation of regression line between yields on temperature using least
square method.
c) Draw the scatter diagram between yield and temperature.
Show the best fitted line on scatter diagram.
e) What percentage of the variable yield can be explained by the variable
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.
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 40 57 112 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. a) Compute the correlation coefficient between yield and temperature. b) Find the equation of regression line between yields on temperature using least square method. c) Draw the scatter diagram between yield and temperature. Show the best fitted line on scatter diagram. e) What percentage of the variable yield can be explained by the variable 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.
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