Apr 19, 2024  
2015-2016 Undergraduate Academic Catalog 
    
2015-2016 Undergraduate Academic Catalog [ARCHIVED CATALOG]

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MA 3320 - Discrete Mathematics II

3 lecture hours 0 lab hours 3 credits
Course Description
This course continues the introduction of discrete mathematics begun in MA 2310 . Emphasis is placed on concepts applied within the field of computer science. Topics include logic and proofs, number theory, counting, computational complexity, computability, and discrete probability. (prereq: MA 2310 , MA 262 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
  • Illustrate by examples proof by contradiction
  • Synthesize induction hypotheses and simple induction proofs
  • Apply the Chinese Remainder Theorem
  • Illustrate by examples the properties of primes
  • Calculate the number of possible outcomes of elementary combinatorial processes such as permutations and combinations
  • Identify a given set as countable or uncountable
  • Derive closed-form and asymptotic expressions from series and recurrences for growth rates of processes
  • Be familiar with standard complexity classes
  • Apply Bayes’ rule and demonstrate an understanding of its implications
  • Apply conditional probability to identify independent events

Prerequisites by Topic
  • Predicate logic
  • Recurrence relations
  • Fundamental structures
  • Continuous probability

Course Topics
  • Course introduction (1 class)
  • Proofs: direct proofs (1 class)
  • Proofs: proof by contradiction (2 classes)
  • Number theory: factorability (1 class)
  • Number theory: properties of primes (1 class)
  • Number theory: greatest common divisors and least common multiples (1 class)
  • Number theory: Euclid’s algorithm (1 class)
  • Number theory: Modular arithmetic (1 class)
  • Number theory: the Chinese Remainder Theorem (1 class)
  • Computational complexity: asymptotic analysis (1 class)
  • Computational complexity: standard complexity classes (1 class)
  • Counting: Permutations and combinations (2 classes)
  • Counting: binomial coefficients (1 class)
  • Countability: Countability and uncountability (2 classes)
  • Countability: Diagonalization proof to show uncountability of the reals (1 class)
  • Discrete probability: Finite probability spaces (1 class)
  • Discrete probability: Conditional probability and independence (2 classes)
  • Discrete probability: Bayes’ rule (1 class)
  • Discrete probability: Random events (1 class)
  • Discrete probability: Random integer variables (1 class)
  • Discrete probability: Mathematical expectation (1 class)
  • Review and exams (4 classes)

Coordinator
Karl David



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