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 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 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 sin

Answer 1

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

Residuals are the differences between observed values and the values predicted by the model. A large absolute value, such as 9.3, indicates a significant discrepancy between the observed and predicted values, suggesting that the model may not fit the data well. Thus, while having both positive and negative residuals is common, the presence of large residuals indicates that the model may not be effective in capturing the trend of the data accurately.