Syllabus:

• Propositional Logic
  • Truth tables
  • Checking tautologies
  • Logical equivalences
  • Consistent sets of formulas
  • Arguments and validity
  • Proofs in mathematics
• Predicate Logic
  • Formulas
  • Meaning
  • Validity
  • Translation
  • Proofs in mathematics
• Sets and Functions
  • Set operations
  • Set identities
  • Relations and equivalences
  • Graphs
• Recursion
  • Recurrence relations
  • Recursive definitions
  • Induction
  • Recursive data structures
• Combinatorics
  • Basic counting techniques
  • Permutations and combinations
  • The pigeonhole principle
  • Counting operations in algorithms
• Algorithms
  • Iterative algorithms
  • Recursive algorithms
  • Algorithm complexity
  • Bounds on complexity
• Applications
  • Social Networks
  • Twelve-Tone Music

  
  Required Textbook:
  

  1. Essentials of Discrete Mathematics, second edition, David J. Hunter, Jones and Bartlett Learning, 2012. ISBN-13978-1-4496-0442-4.

  
  Recommended Textbook:
  

  1. Stephen B. Maurer, Anthony Ralston, Discrete Algorithmic Mathematics , 3rd Edition,A K Peters Ltd, 2004.
  2. Kenneth H. Rosen, Discrete mathematics and its applications, 7th ed. ISBN 978-0-07-338309-5.

  Handouts and Homework: All handouts and homework assignments will be posted on Oncourse.

  Associate Instructors:

  Eriya Terada eterada@umail.iu.edu, lab session on Thursday, 5:45 pm - 7:40 pm, I2 122.
  Office hours: Mondays 1:00-2:00 in LH 406.

  Josh Hieronymus jhierony@indiana.edu, lab sessions on Friday, 11:15 am - 1:10 pm, I2 130.
  Office hours: Tuesdays 12:30-1:30 in LH 406.

  Jaime Guerrero jaiguerr@umail.iu.edu, lab sessions on Friday, 1:25 pm - 3:20 pm, I2 130.
  Office hours: Wednesdays 1:30-2:30 in LH 406.

Grading:

• Homework assignments: 15%
• There will be weekly homework.
• Each homework will consist of the following parts:
  1. Regular problems: A set of problems chosen from several sources including the textbooks above.
  2. Reading assignment from the textbook or other handouts.
  3. Computer problems that might require the use of a software.
• Each homework will be assigned on a Thursday and will be due the Thursday after, in class.
• Solutions must be written LEGIBLY.
• It is encouraged to discuss the problem sets with others, but everyone needs to turn in a unique personal write-up.
• Minitests: 25%
• During each lab except for those during exam weeks there will be a minitest, based mainly on the homework assignment due that same week.
• During each lab there will also be collective problem solving sessions organized by the AIs.
• There will be NO make-up tests. However, the lowest test grade will be dropped.
• Each lab session will include a discussion of the homework problems due that same week. In addition, you are welcome to discuss any other problems you need to with your AI.
• Midterm I: 15%
• Midterm I is scheduled on 10/10/13.
• Midterm II: 15%
• Midterm II is scheduled on 11/14/13.
• Final exam: 30%.
• Final exam is scheduled at 12:30-2:30 p.m., Thurs., December 19.
• We will have a closed book, closed-note exam. However, you are allowed to bring your letter-size cheat sheet to the exam.

Ground rules:

• I strongly advise you to attend all the classes and take good notes.
• NO make-up minitests. However, the lowest grade will be dropped.
• Late homework will NOT be accepted. However, the lowest homework grade will be dropped.
• There will be NO make-up midterm exams.
• Calculators are NOT allowed during the midterm and final exams. However, you can bring a letter-size sheet with notes and formulas.
• The final grade will be calculated according to the evaluation scheme given above and these grades will then be curved to determine your letter grades. However if you get less that 25/100 on the final exam or your total grade is less than 45/100 your final grade will automatically be an F.
• NO Incomplete grades will be given under any condition.
• NO extra work, extra credit or anything outside the regular homeworks and minitests will be assigned. Please plan your study strategy during the term accordingly.
• Grading mistakes:
  If during the semester you feel there has been a mistake made in your grading by the AIs, please contact them first. If after meeting with the AIs you still feel there is a problem with the marking, please contact me.
• Collaborative work:
  One of the best ways to learn new material is to collaborate in groups. You may discuss the homework problems with your classmates, and in this way make the learning process more enjoyable. However, the homework you hand in must be your own work, in your own words and your own explanation.
• Here is the link to The Code of Student Conduct.