The predicted value and residual for y is 9.4 and -0.4 respectively.
In statistics, a regression equation is used to determine whether or not there is a relationship between two sets of data. If you measure a child's height every year, you might discover that they grow about 3 inches per year. A regression equation can be used to model that trend (growing three inches per year). In fact, most things in the real world (from gas prices to hurricanes) can be modelled mathematically, allowing us to forecast future events.
Regression equations can assist you in determining whether your data can be fit to an equation. This is extremely useful if you want to make predictions based on your data, whether they are future predictions or indications of past behaviour.
Given,
Regression equation is y=11-038x
Observed value of y = 9
predicted value of y can be determined by substituting x=2 in the equation
y=11-0.8(2)=11-1.6=9.4
The residual can be calculated by formula,
residual = observed value - predicted value
residual = 9 - 9.4
residual = -0.4
Thus, the predicted value is 9.4 and residual is -0.4.
To learn more about residual refer here
https://brainly.com/question/17438811
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Your question is incomplete, here is the complete question.
suppose the estimated regression equation is given by y=11-0.8x . what are the predicted value of y and the residual when x is 2 and y is observed to be 9?
