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When graphing the residual values, when do you know if a linear model is an appropriate model for your data?

A)If the points in the residual plot are all close to the vertical axis.
B)If the points in the residual plot are all in a straight line.
C)If the points in the residual plot are scattered.
D)If the points in the residual plot are all close to the horizontal axis.

Respuesta :

anshu19

Answer:

The correct answer is C

Step-by-step explanation:

If we see a curved relationship in the residual plot, the linear model is not appropriate. Another type of residual plot shows the residuals versus the explanatory variable.

When graphing the residual values, you know if a linear model is an appropriate model for your data if the points in the residual plot are scattered.

What is residual plot?

A residual is a measure of how far away a point is vertically from the regression line. Simply, it is the error between a predicted value and the observed actual value.

A residual plot is a graph that shows the residuals on the y axis and the independent variable on the x axis.

The goodness of fit of a linear model is depicted by the pattern of the graph of a residual plot. If each individual residual is independent of each other, i.e., they create a random pattern together.

Learn more about residual plot here

https://brainly.com/question/2876516

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