The Universe of Possibilities
Imagine you are standing in a vast, open field. In the world of probability, we call this field our sample space, denoted by S. It is the grand stage where every possible outcome of an experiment resides.
Within this space, we have two events, C and D. The problem provides a crucial constraint: C⊂D.
This is a geometric reality. It means that every single outcome that makes event C happen is also an outcome that makes event D happen. If C occurs, D is guaranteed to occur.
The Conditional Lens
We are asked to evaluate P(C∣D), the probability of C given that D has already occurred. This is the heart of conditional probability, defined by the following formula:
This formula tells us that when we know D has occurred, our "universe" has shrunk. We no longer care about the parts of S that are outside D; our new sample space is restricted to D.
The Geometry of Intersection
Now, consider the numerator: P(C∩D). Because we know C⊂D, the intersection of C and D is simply C itself.
Every point in C is already contained within D. Therefore, the overlap is just C, which simplifies our expression:
Substituting this back into our conditional probability formula, we obtain:
The Algebraic Twist
We are given that $P(D)
eq 0$. Since P(D) is a probability, we know that 0<P(D)≤1.
Consider the term P(D)1. In all cases where P(D)≤1, the reciprocal must satisfy the following inequality:
The Final Intuition
We have established that P(C∣D)=P(C)⋅P(D)1. Since P(D)1≥1, multiplying P(C) by this factor can only make it larger or keep it the same.
Therefore, we arrive at the final result:
This result is intuitive. If you know that a larger event D has occurred, and C is a subset of D, the likelihood of C happening is higher than it was before you knew anything about D. You have eliminated the "noise" outside of D, making the occurrence of C more probable.