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Newest Discrete Mathematics with Applications summaries
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CHAPTER 5: SEQUENCES, MATHEMATICAL INDUCTION, AND RECURSION
- Answers • 155 pages • 2020
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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 16 - Random Variable
- Lecture notes • 26 pages • 2018
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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 14 - Intro to Combinatory
- Lecture notes • 44 pages • 2018
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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 notes • 34 pages • 2018
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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 10 - Intro to Graph
- Lecture notes • 17 pages • 2018
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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 notes • 43 pages • 2018
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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 notes • 34 pages • 2018
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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 07 - Induction
- Lecture notes • 15 pages • 2018
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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 17 - Discrete Distribution
- Lecture notes • 29 pages • 2018
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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 15 - Intro to Probability
- Lecture notes • 29 pages • 2018
- Available in package deal
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- £6.16
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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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