How to Prove It - A Structured Approach

Helps students transition from problem solving to proving theorems, with a new chapter on number theory and over 150 new exercises.

Table des matières

1. Sentential logic; 2. Quantificational logic; 3. Proofs; 4. Relations; 5. Functions; 6. Mathematical induction; 7. Number theory; 8. Infinite sets.

A propos de l'auteur

Daniel J. Velleman is Julian H. Gibbs '46 Professor of Mathematics, Emeritus at Amherst College, and was a professor at Amherst College from 1983 to 2017. He received his B.A. from Dartmouth College in 1976, and his Ph.D. from the University of Wisconsin, Madison in 1980. His other books include Which Way Did the Bicycle Go? (with Stan Wagon and Joe Konhauser, 1996), Philosophies of Mathematics (with Alexander George, 2002), and Calculus: A Rigorous First Course (2016). Among his awards and distinctions are the Chauvenet Prize, the Paul R. Halmos–Lester R. Ford Award, the Carl B. Allendoerfer Award, and the Chandler Davis Prize for Expository Excellence. He was Editor of Dolciani Mathematical Expositions from 1999 to 2004 and the American Mathematical Monthly from 2007 to 2011.

Résumé

Proofs play a central role in advanced mathematics and theoretical computer science, and this bestselling text's third edition will help students transition from solving problems to proving theorems by teaching them the techniques needed to read and write proofs, with a new chapter on number theory and over 150 new exercises.

Détails du produit

• Auteurs: Daniel J. Velleman, Daniel J. (Amherst College Velleman, Velleman Daniel J.
• Edition: Cambridge University Press ELT
• Langues: Anglais
• Format d'édition: Livre Relié
• Sortie: 30.09.2019
• EAN: 9781108424189
• ISBN: 978-1-108-42418-9
• Pages: 468
• Catégories: Sciences naturelles, médecine, informatique, technique > Mathématiques > Bases; Sciences sociales, droit, économie > Médias, communication > Librairies, bibliothèques; COMPUTERS / Information Theory, MATHEMATICS / Logic, MATHEMATICS / Discrete Mathematics, COMPUTERS / Programming / Algorithms, MATHEMATICS / Set Theory, algorithms and data structures, Discrete Mathematics, Algorithms & data structures, Information theory, Coding theory & cryptology, Mathematical logic, Coding theory and cryptology, Set theory