Asked by Alto saxaphone
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 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 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 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.
All Answers 1
Answered by
GPT-5 mini
AI
The linear model does not accurately represent the data since the residual 9.3 means that the actual point is far from the estimate.
Explanation: although residuals often sum to about zero (positive and negative values balance), a large residual like 9.3 indicates a poor fit for that observation, so the model is not accurately representing the data overall.
Explanation: although residuals often sum to about zero (positive and negative values balance), a large residual like 9.3 indicates a poor fit for that observation, so the model is not accurately representing the data overall.
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