There are different probability rules like a complementary rule, difference rule, inclusion-exclusion rule, conditional probability, etc. Let’s take a look at these rules in detail,
Let’s consider A and B are the likely happening event. According to Inclusion-Exclusion Rule:
Question1: If the probability of having green eyes is 10%, the probability of having brown hair is 75%, and the probability of being a green-eyed brown-haired person is 9%, let us assume, A as green eyes and B as brown hair, what is the probability of:
The probability of a student passes math course is 1/3 and passes statics course is 1/4. If the probability to pass both courses is 1/6. What is the probability to pass one of both courses?
The probability of passing at least one class is 1 minus the probability of failing both.
A key point of ambiguity in the problem statement is “a student”. If the problem is stating that students in general have these probabilities of passing, you might think that results for the three subjects are highly correlated, because they are all driven by overall intelligence. In the extreme, you might say that the 1/3 of the students who pass English would be the smart ones, and they would also pass math and science. This would make the answer be 1/3.
P ( A U B U C )=> A or B or C or all 3.
If the three outcomes are correlated, the answer could be as high as 1/3 (33% ); or if they are anti-correlated, the answer could be zero.
Let us take an example of a class of 35. Thus, 10/35 would pass algebra and 14/35 would pass geometry. So, it would not be possible for 15/35 to pass BOTH exams since that cannot be higher than either of the total who passed EACH exam.
Using the complement is often the easiest and quickest method.