Answer:
The residual value when x=2 is -1
Step-by-step explanation:
The difference between the observed value of the dependent variable and the predicted value is called the residual (e). Every data point has one residual. Lesser the residual value, better the best fit line is.
Mathematically,
\(e = y-\hat y\)
Here from the graph,
the observed value is 2, so y=1
the predicted value is 0.5(2)+1 = 1+1 = 2, so \(\hat y=2\)
Putting the values,
\(e = 1-2=-1\)
