Conditional Probability, Bayes’ formula, Radar Accuracy, Medical Diagnosis
Abstract
In statistics, the concept of probability is very important, and the knowledge of probability can significantly assist people in their daily lives, helping them make better decisions in uncertainty and risk assessment. In real life, because there are various prerequisites, people often use conditional probability more frequently. Bayes’ theorem is an important conclusion in conditional probability. This paper focuses on Bayes’ theorem to solve two simple problems respectively from the military and medical fields. The first problem is about radar false alarm rate. This paper simulated a radar system, which has a 95% accuracy rate and a 10% false alarm rate. Then this paper assumes the probability of enemy aircraft presence in a region is 5%. Under the above conditions, the author calculates the actual probability and research. The second problem is about medical diagnosis. The author assumes a medical test of a certain disease has 99% sensitivity and 95% specificity. The prevalence of this disease is 1%. Similarly, calculate and study these situations. This paper aims at illustrating the practical application of Bayes’ theorem through these two examples.
