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Let \(C_{1}, C_{2}, C_{3}\) be independent events with probabilities \(\frac{1}{2}, \frac{1}{3}, \frac{1}{4}\), respectively. Compute \(P\left(C_{1} \cup C_{2} \cup C_{3}\right)\).

Short Answer

Expert verified
The probability of the union of the three events \(C_{1}\), \(C_{2}\), and \(C_{3}\) is \(\frac{3}{4}\).

Step by step solution

01

Note Each Event Probabilities

We have three independent events given: \(C_{1}\) with probability \(\frac{1}{2}\), \(C_{2}\) with probability \(\frac{1}{3}\), and \(C_{3}\) with probability \(\frac{1}{4}\).
02

Use the Principle of Inclusion-Exclusion

The Principle of Inclusion-Exclusion states that for three events \(A\), \(B\), and \(C\), the probability of their union is given by \(P(A ∪ B ∪ C) = P(A) + P(B) + P(C) – P(A ∩ B) – P(A ∩ C) – P(B ∩ C) + P(A ∩ B ∩ C)\). Here, since the events are independent, the intersection of any two or all three events can be expressed as a product of their respective probabilities.
03

Compute the Probabilities of Intersections

Calculate \( P(C_{1} ∩ C_{2}) = P(C_{1}) \times P(C_{2}) = \frac{1}{2} \times \frac{1}{3} = \frac{1}{6}\). Similarly, compute \(P(C_{1} ∩ C_{3}) = P(C_{1}) \times P(C_{3}) = \frac{1}{2} \times \frac{1}{4} = \frac{1}{8}\), and \(P(C_{2} ∩ C_{3}) = P(C_{2}) \times P(C_{3}) = \frac{1}{3} \times \frac{1}{4} = \frac{1}{12}\). For all three, \(P(C_{1} ∩ C_{2} ∩ C_{3}) = P(C_{1}) \times P(C_{2}) \times P(C_{3}) = \frac{1}{2} \times \frac{1}{3} \times \frac{1}{4} = \frac{1}{24}\).
04

Put the Calculated Values to Principle of Inclusion-Exclusion Formula

Substitute the calculated values into the formula, \(P(C_{1} ∪ C_{2} ∪ C_{3}) = P(C_{1}) + P(C_{2}) + P(C_{3}) – P(C_{1} ∩ C_{2}) – P(C_{1} ∩ C_{3}) – P(C_{2} ∩ C_{3}) + P(C_{1} ∩ C_{2} ∩ C_{3}) = \frac{1}{2} + \frac{1}{3} + \frac{1}{4} - \frac{1}{6} - \frac{1}{8} - \frac{1}{12} + \frac{1}{24}.\)
05

Simplify the Formula to Get the Result

Simplify the above equation to get the result. The LCD is 24. Express each term over the common denominator, and then sum and simplify: \(= \frac{12}{24} + \frac{8}{24} + \frac{6}{24} - \frac{4}{24} - \frac{3}{24} - \frac{2}{24} + \frac{1}{24} = \frac{18}{24} = \frac{3}{4}\).

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Most popular questions from this chapter

Assume that \(P\left(A_{1} \cap A_{2} \cap A_{3}\right)>0\). Prove that $$ P\left(A_{1} \cap A_{2} \cap A_{3} \cap A_{4}\right)=P\left(A_{1}\right) P\left(A_{2} \mid A_{1}\right) P\left(A_{3} \mid A_{1} \cap A_{2}\right) P\left(A_{4} \mid A_{1} \cap A_{2} \cap A_{3}\right) . $$

Let \(X\) be a random variable with space \(\mathcal{D}\). For \(D \subset \mathcal{D}\), recall that the probability induced by \(X\) is \(P_{X}(D)=P[\\{c: X(c) \in D\\}] .\) Show that \(P_{X}(D)\) is a probability by showing the following: (a) \(P_{X}(\mathcal{D})=1\). (b) \(P_{X}(D) \geq 0\). (c) For a sequence of sets \(\left\\{D_{n}\right\\}\) in \(\mathcal{D}\), show that $$ \left\\{c: X(c) \in \cup_{n} D_{n}\right\\}=\cup_{n}\left\\{c: X(c) \in D_{n}\right\\} $$ (d) Use part (c) to show that if \(\left\\{D_{n}\right\\}\) is sequence of mutually exclusive events, then $$ P_{X}\left(\cup_{n=1}^{\infty} D_{n}\right)=\sum_{n=1}^{\infty} P_{X}\left(D_{n}\right) $$

From a bowl containing five red, three white, and seven blue chips, select four at random and without replacement. Compute the conditional probability of one red, zero white, and three blue chips, given that there are at least three blue chips in this sample of four chips.

Let us select five cards at random and without replacement from an ordinary deck of playing cards. (a) Find the pmf of \(X\), the number of hearts in the five cards. (b) Determine \(P(X \leq 1)\).

A bowl contains 10 chips numbered \(1,2, \ldots, 10\), respectively. Five chips are drawn at random, one at a time, and without replacement. What is the probability that two even-numbered chips are drawn and they occur on even- numbered draws?

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