• Course Catalog Description
  
  • Introduction to probability. Discrete and continuous random variables and their distributions. Simulations of random variables. Descriptive statistics. Statistical inference. Regression. Monte Carlo methods. Stochastic processes. Queuing systems.
  
  
• Section 1 Lecture Time/Place
  
  • First meeting on February 14, Thursday at 13:40 in BMB-4
  • Mondays - 10:40 to 12:30 in BMB-2
  • Thursdays - 13:40 to 14:30 in BMB-4
  
  
• Syllabus
  
  
• Course Objectives
  
  • At the end of this course, the students will be able to:
    • analyze and interpret large scale data,
    • apply probability theory and statistics to handle uncertainty,
    • infer facts and relationships from collected data, and
    • construct simulations by sampling from arbitrary distributions.
    The course will provide the students the ability to apply knowledge of mathematics, science, and engineering; therefore, supporting the corresponding student outcome.
  
  
• Prerequisites
  
  • MATH 120 - Calculus of Functions of Several Variables


• Reading Material
  
  • Textbook:
    Probability and Statistics for Computer Scientists, Second Edition, Michael Baron, 2013, 978-1439875902
    
    
    
  • Additional readings:
    • Introduction to Probability, Statistics, and Random Processes. Hossein Pishro-Nik, 2014, 978-0990637202
    • Probability Theory: The Logic of Science, E. T. Jaynes, 2003, 978-0521592710
    • Probability and Random Processes, Grimmett, Geoffrey, and David Stirzaker, 2001, 978-0198572220
    • Probability and Statistics with Reliability, Queuing, and Computer Science Applications, Kishor S. Trivedi, 2001, 978-0471333417


• Grading Policy
  
  • 4 assignments (5% each): 20%
  • Midterm exam : 40%
  • Final exam : 40%

Tolga Can   (tcan@ceng.metu.edu.tr)
Office Location: Computer Engineering, B-109
Office Hours: By appointment. Contact the instructor