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A true negative result occurs when a test correctly identifies a subject as not having the condition being tested for. In the context of drug testing, it means that the test accurately indicates that a person does not use marijuana when they actually do not. Understanding true negatives is crucial for evaluating the effectiveness of a test and calculating its accuracy.

False positives and false negatives are critical concepts in diagnostic testing. A false positive occurs when a test incorrectly indicates the presence of a condition (e.g., a positive drug test for someone who does not use drugs), while a false negative indicates the absence of a condition when it is actually present. These concepts help in assessing the reliability of a test and understanding its implications in real-world scenarios.

A contingency table is a statistical tool used to summarize the relationship between two categorical variables. In this case, it can be used to organize the results of the drug test, showing the counts of true positives, true negatives, false positives, and false negatives. This visual representation aids in calculating various statistics, such as sensitivity and specificity, which are essential for evaluating the test's performance.