6. Missing data, nonrandom samples, and outlying observations True or False: If the data for an observation on either the dependent variable or one of the independent variables are missing at random, then the size of the random sample available from the population must be reduced, which reduces the estimator's precision and introduces a bias.

False

Step-by-step explanation:

The answer to this question is false because the missing observation does not introduce bias to the estimator. But missing observations reduces the size of the sample that is available from the given population. Therefore reducing the precision of the estimators.

In conclusion, no bias is introduced because of missing observations so the answer is false.