Answer:
Step-by-step explanation:
Given is a table of values of x and y.
X represents the number of hours ten randomly selected students spent studying and Y their corresponding midterm exam grades.
x y
0 65
1 70
1.5 77
2 79
2.5 83
3.4 91
5 92
5 94
5.5 95
6 98
Correlation 0.973459204
Since correlation is near to 1, there is a linear association and hence regression linear line can be fitted.
a) [tex]slope = 5.273[/tex]
b) [tex]y intercept = 67.579[/tex]
c) [tex]Regression line is y = 5.273x+67.579[/tex]
Substitute x =5
[tex]y(5) = 5.273(5)+67.579\\=93.944[/tex]
d) when x =2
[tex]y(2) = 78.125[/tex]
Actual value for x=2 is 79
Error = Actual - estimated
= [tex]79-78.125\\=0.875[/tex]