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MAT 230 - Discrete Mathematics- Problem Set 7-3 Exam Two | SNHU | Grade A

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This document includes complete, step-by-step solutions for MAT 230 Discrete Mathematics Problem Set 7–3 Exam Two at Southern New Hampshire University (SNHU), aligned with Exam Two content. It covers advanced discrete mathematics topics from the second half of the course, explained clearly to support strong conceptual understanding and exam preparation. The assignment earned a Grade A and is ideal as a study guide and reference for mastering Exam Two material.

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Institution
Discrete Mathematics
Course
Discrete Mathematics









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Institution
Discrete Mathematics
Course
Discrete Mathematics

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Uploaded on
December 22, 2025
Number of pages
15
Written in
2025/2026
Type
Exam (elaborations)
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MAT 230 EXAM TWO


This document is proprietary to Southern New Hampshire University. It and the problems within
may not be posted on any non-SNHU website.




TESTBANKSNERD




1

, Directions: Type your solutions into this document and be sure to show all steps for arriving at
your solution. Just giving a final number may not receive full credit.



PROBLEM 1
This question has 2 parts.


Part 1: Suppose that F and X are events from a common sample space with P (F ) /= 0 and P (X) /= 0.

(a) Prove that P (X) = P (X|F )P (F ) + P (X|F¯)P (F¯). Hint: Explain why P (X|F )P (F ) =
P (X ∩ F ) is another way of writing the definition of conditional probability, and then use
that with the logic from the proof of Theorem 4.1.1.



P (X) = P (X | F )P (F ) + P (X | F )P (F )
As a proof, by definition of conditional probability
P (X ∩ F )
P (X | F ) = P (F ) =⇒ P (X ∩ F ) = P (X | F )P (F )

and
P (X ∩ F )
P (X | F ) = PF ) =⇒ P (∩F ) = P (X | F )P (F )
P (F )


X = (X ∩ F ) ∪ (X ∩ F )
and sets (X ∩ F ) and (X ∩ F ) are disjoint, we have

P (X) = P (X ∩ F ) + P (X ∩ F )
Substituting

P (X) = P (X | F )P (F ) + P (X | F )P (F )




(b) Explain why P (F |X) = P (X|F )P (F )/P (X) is another way of stating Theorem 4.2.1 Bayes
Theorem.

Baye’s theorem states that

P (X | F )P (F )
P (F | X) =
P (X)
By the definition of conditional probability

P (F ∩ X)
P (F | X) =
P (X)
which is Baye’s theorem.

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