we have
the values in Rita’s data set. are
(1, 19), (2, 33), (4,45), (5, 57), (6,71.5)
yˆ=9.7x+10.3--------> the equation of a linear regression line
we know
the residual, is when you subtract the predicted value from the observed value.
Residual = [Observed – Predicted]
Part 1) (1, 19)
x=1
observed value=19
predicted value=9.7x+10.3------> 9.7*1+10.3------> 20
Residual = [19-20]=-1
point (1,-1)
Part 2) (2, 33)
x=2
observed value=33
predicted value=9.7x+10.3------> 9.7*2+10.3------> 29.7
Residual = [33-29.7]=3.3
point (2,3.3)
Part 3) (4, 45)
x=4
observed value=45
predicted value=9.7x+10.3------> 9.7*4+10.3------> 49.1
Residual = [45-49.1]=-4.1
point (4,-4.1)
Part 4) (5, 57)
x=5
observed value=57
predicted value=9.7x+10.3------> 9.7*5+10.3------> 58.8
Residual = [57-58.8]=-1.8
point (5,-1.8)
Part 5) (6, 71.5)
x=6
observed value=71.5
predicted value=9.7x+10.3------> 9.7*6+10.3------> 68.5
Residual = [71.5-68.5]=2.5
point (6,2.5)
Part 6)
graph the residual plot for the data set.
Round residuals to the nearest unit
the residual points are
(1,-1)
(2,3)
(4,-4)
(5,-2)
(6,3)
see the attached figure
