The predicted calories in food items based on grams of carbs are represented by the residual plot.

Residual plot with x-axis labeled carbs in grams and y-axis labeled residuals. There are eight points plotted 5 and 0, 7 and negative 15, 8 and 25, 10.5 and negative 22.5, 11 and 5, 12 and 0, 12.5 and 12.5, and 14 and negative 5.

What does the pattern in the residual plot indicate about the type of model? (4 points)

Group of answer choices

The pattern is random, indicating a good fit for a nonlinear model.

The pattern is random, indicating a good fit for a linear model.

The pattern shows the points are far from the zero line, indicating a good fit for a linear model.

The pattern shows the points are far from the zero line, indicating a good fit for a nonlinear model.

The plot of the residual which is obtained by plotting the residual values against the independent variable is used to determine the appropriateness of a linear model for a set of data. Since, the residual plot is randomly distributed, then the linear model is a good fit (B).

Therefore, since the model shows a random distribution of points, then linear model is a good fit.

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The pattern is random, indicating a good fit for a linear model.

Step-by-step explanation:

The residuals are the difference between the actual value and the expected value.

If a linear model is a good fit, the residual pattern will be random, with most of the points close to the x-axis, and the same number of positive residuals as negative residuals.

b

step-by-step explanation:

a difference is the result of subtraction. while each of these expressions has subtraction in it, a difference will be the result when subtraction is the last operation applied in the order of operations for the expression. this means subtraction must be outside of the parenthesis. only b has this.