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Newest Discrete Mathematics with Applications summaries

CHAPTER 5: SEQUENCES, MATHEMATICAL INDUCTION, AND RECURSION CHAPTER 5: SEQUENCES, MATHEMATICAL INDUCTION, AND RECURSION

  • CHAPTER 5: SEQUENCES, MATHEMATICAL INDUCTION, AND RECURSION

  • Answers • 155 pages • 2020
  • Available in package deal
    • This document is containing selected question of chapter 5 for all the young IT aspirants who want to keep learning new things and new questions. I hope this document can help you in verifying your solutions and learning new things. Please feel free to post any new solutions or any doubts.This blog will be updated as new and good solutions are posted by you geeks.
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Lecture 14 - Intro to Combinatory Lecture 14 - Intro to Combinatory

  • Lecture 14 - Intro to Combinatory

  • Class notes • 44 pages • 2018
  • Available in package deal
    • The outcome of this course is able to perform basic operations on discrete structures, able to interpret logic and construct proofs, able to interpret various concepts on graphs and employ related algorithms and last but not least, able to apply principles of discrete probability to calculate probabilities and expectations of simple random processes.
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Lecture 04 - Propositional Logic Lecture 04 - Propositional Logic

  • Lecture 04 - Propositional Logic

  • Class notes • 34 pages • 2018
  • Available in package deal
    • The outcome of this course is able to perform basic operations on discrete structures, able to interpret logic and construct proofs, able to interpret various concepts on graphs and employ related algorithms and last but not least, able to apply principles of discrete probability to calculate probabilities and expectations of simple random processes.
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Lecture 16 - Random Variable Lecture 16 - Random Variable

  • Lecture 16 - Random Variable

  • Class notes • 26 pages • 2018
  • Available in package deal
    • The outcome of this course is able to perform basic operations on discrete structures, able to interpret logic and construct proofs, able to interpret various concepts on graphs and employ related algorithms and last but not least, able to apply principles of discrete probability to calculate probabilities and expectations of simple random processes.
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Lecture 18 - Normal Distribution Lecture 18 - Normal Distribution

  • Lecture 18 - Normal Distribution

  • Class notes • 26 pages • 2018
  • Available in package deal
    • The outcome of this course is able to perform basic operations on discrete structures, able to interpret logic and construct proofs, able to interpret various concepts on graphs and employ related algorithms and last but not least, able to apply principles of discrete probability to calculate probabilities and expectations of simple random processes.
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Lecture 01 - Set Theory Lecture 01 - Set Theory

  • Lecture 01 - Set Theory

  • Class notes • 24 pages • 2018
  • Available in package deal
    • The outcome of this course is able to perform basic operations on discrete structures, able to interpret logic and construct proofs, able to interpret various concepts on graphs and employ related algorithms and last but not least, able to apply principles of discrete probability to calculate probabilities and expectations of simple random processes.
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Lecture 09 - Intro to Complexity of An Algorithm Lecture 09 - Intro to Complexity of An Algorithm

  • Lecture 09 - Intro to Complexity of An Algorithm

  • Class notes • 21 pages • 2018
  • Available in package deal
    • The outcome of this course is able to perform basic operations on discrete structures, able to interpret logic and construct proofs, able to interpret various concepts on graphs and employ related algorithms and last but not least, able to apply principles of discrete probability to calculate probabilities and expectations of simple random processes.
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Lecture 12 - Tree Lecture 12 - Tree

  • Lecture 12 - Tree

  • Class notes • 21 pages • 2018
  • Available in package deal
    • The outcome of this course is able to perform basic operations on discrete structures, able to interpret logic and construct proofs, able to interpret various concepts on graphs and employ related algorithms and last but not least, able to apply principles of discrete probability to calculate probabilities and expectations of simple random processes.
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Lecture 02 - Relation Lecture 02 - Relation

  • Lecture 02 - Relation

  • Class notes • 43 pages • 2018
  • Available in package deal
    • The outcome of this course is able to perform basic operations on discrete structures, able to interpret logic and construct proofs, able to interpret various concepts on graphs and employ related algorithms and last but not least, able to apply principles of discrete probability to calculate probabilities and expectations of simple random processes.
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Lecture 05 - Predicate Logic Lecture 05 - Predicate Logic

  • Lecture 05 - Predicate Logic

  • Class notes • 34 pages • 2018
  • Available in package deal
    • The outcome of this course is able to perform basic operations on discrete structures, able to interpret logic and construct proofs, able to interpret various concepts on graphs and employ related algorithms and last but not least, able to apply principles of discrete probability to calculate probabilities and expectations of simple random processes.
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