Jade was working on her statistics homework. One of the questions gave her a trend line and asked her to find the residuals. She found the following residuals 2.6, 9.3,−5.489

Question

, and −6.59
. What conclusion can Jade make about the linear model based on the residuals?(1 point)
Responses

The linear model does not accurately represent the data since the residual 9.3 means that the actual point is far from the estimate.
The linear model does not accurately represent the data since the residual 9.3 means that the actual point is far from the estimate.

The linear model seems to accurately represent the data since half of the residuals are positive and half of the residuals are negative.
The linear model seems to accurately represent the data since half of the residuals are positive and half of the residuals are negative.

The linear model does not accurately represent the data since half of the residuals are positive and half of the residuals are negative.
The linear model does not accurately represent the data since half of the residuals are positive and half of the residuals are negative.

The linear model seems to accurately represent the data since the residual 2.6 means that the actual point is not far from the estimate.

Answer 1

Based on the residuals provided (2.6, 9.3, -5.489, and -6.59), the best conclusion Jade can make about the linear model is:

The linear model does not accurately represent the data since the residual 9.3 means that the actual point is far from the estimate.

This is because a residual of 9.3 indicates that there is a significant difference between the actual data point and the estimate given by the linear model, suggesting that the model is not fitting the data well overall. While having both positive and negative residuals shows that the model is making both over and under estimations, the presence of a large positive residual like 9.3 signals that the fit might not be adequate.