Use the following to answer the question(s) below.
Weekly commodity prices for heating oil (in cents) were obtained and regressed against time. Below is the regression output and residual plots from fitting a linear model.
-Which of the following statement is true?
A) The normal probability plot shows no bend and indicates that Independence assumption is satisfied.
B) The residual plot has no pattern and indicates that Independence assumption is satisfied.
C) The histogram is relatively bell-shaped and indicates that Independence assumption is satisfied.
D) The t-test for the regression slope indicates that Independence assumption is satisfied.
E) The histogram and plots show that not all assumptions and conditions for regression inference are met. It looks like data are highly correlated over time. So, we should test the model for autocorrelation.

Question

Use the following to answer the question(s) below.
Weekly commodity prices for heating oil (in cents) were obtained and regressed against time. Below is the regression output and residual plots from fitting a linear model.    
-Which of the following statement is true?
A) The normal probability plot shows no bend and indicates that Independence assumption is satisfied. 
B) The residual plot has no pattern and indicates that Independence assumption is satisfied. 
C) The histogram is relatively bell-shaped and indicates that Independence assumption is satisfied. 
D) The t-test for the regression slope indicates that Independence assumption is satisfied. 
E) The histogram and plots show that not all assumptions and conditions for regression inference are met. It looks like data are highly correlated over time. So, we should test the model for autocorrelation.

Quizplus · Accepted Answer

The histogram is not enough to indicate that the Independence assumption is satisfied. The residual plot shows some pattern and may indicate that the Independence assumption is not satisfied. The normal probability plot also appears to have some bend, suggesting non-normality. Additionally, the plots suggest that there may be autocorrelation in the data, meaning that the errors are not independent over time. Therefore, we should test the model for autocorrelation.

Use the Following to Answer the Question(s) Below