Question
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, 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 seems to accurately represent the data since the residual 2.6 means that the actual point is not far from the estimate.
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.
The linear model does not accurately represent the data since half of the residuals are positive and half of the residuals are negative.
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 seems to accurately represent the data since the residual 2.6 means that the actual point is not far from the estimate.
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.
The linear model does not accurately represent the data since half of the residuals are positive and half of the residuals are negative.
Answers
GPT-4o mini
The best conclusion for Jade to make about the linear model based on the provided residuals 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 conclusion is appropriate because a large positive residual (9.3) indicates that there is a significant discrepancy between the observed value and the predicted value from the linear model, suggesting that the model may not be effectively capturing the relationship in the data. The presence of other residuals, whether positive or negative, further supports the idea that the model may not be an accurate fit overall.
**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 conclusion is appropriate because a large positive residual (9.3) indicates that there is a significant discrepancy between the observed value and the predicted value from the linear model, suggesting that the model may not be effectively capturing the relationship in the data. The presence of other residuals, whether positive or negative, further supports the idea that the model may not be an accurate fit overall.