Answer:
C. A residual is the difference between the observed y-value of a data point and the predicted y-value on a regression line for the x-coordinate of the data point. A residual is positive when the point is above the line, negative when it is below the line, and zero when the observed y-value equals the predicted y-value.
Step-by-step explanation:
The residuals are obtained when there is some difference between the observed values and the fitted values of the data. Suppose we want to make a curve or hyperbola but the observed data does not actually give the curve required or there is some difference between the observed values and fitted values. The square of the sum of these differences is called residual.
The residual is positive when the point is above the line, negative when it is below the line, and zero when the observed y-value equals the predicted y-value.
Residual is obtained by subtracting the predicted value from observed value.This difference called the <u>residual</u> is
- positive when the observed value > predicted value
<em>For a positive value the point lies above the (fitted) line.</em>
- negative when the observed value < predicted value
<em>For a negative value the point lies below the (fitted) line.</em>
- zero when the observed value = predicted value
<em>For a zero value the point lies on the (fitted) line.</em>
Step-by-step explanation:
