Question

Which of the following statements is correct about complete information?

a. Complete information is not necessary if there is multicollinearity in the model
b. If we do not have complete information, R will give us an error message automatically
c. As long as we have all values of at least one predictor, we have complete information
d. If we do not have complete information, our model is likely to make poor predictions

Answer 1

Complete information is crucial in statistical modeling to ensure accurate and reliable predictions. If we do not have complete information, our model is likely to make poor predictions.

Step-by-step explanation:

Complete information is crucial in statistical modeling to ensure accurate and reliable predictions. The correct statement about complete information is option d: If we do not have complete information, our model is likely to make poor predictions. When we have incomplete information, there are missing values or missing predictors that can lead to biased and unreliable predictions.