CSE103 - A Practical Introduction to Probability and Statistics

CSE 103 can be used as an alternative to Math 183. CSE 103 is not duplicate of ECE 109, ECON 120A or Math 183. Traditionally, computer algorithms have been designed to correctly process any input from a set of allowable inputs. This is reflected in the emphasis that computer science education places on logic, discrete math and worst-case analysis. On the other hand, the actual performance of computers in terms of speed, memory and power consumption, and increasingly also correctness, depends on the distribution of the data it receives as input. It is becoming critically important for software and hardware developers to employ statistical methods in the design and analysis of the systems that they develop. This need is most apparent in areas such as computer vision, machine learning and bio-informatics. It is also becoming increasingly important in traditional areas of computer science such as communication protocols, memory management, computer architecture and databases.

Course Topics: Distribution over the real line. Independence, expectation, conditional expectation, mean, variance, Hypothesis testing. Learning classifiers. Distributions over R^n, covariance matrix, Binomial, Poisson distributions. Chernoff bound. Entrophy. Compression. Arithmetics coding. Maximal likelihood estimation. Bayesian estimation.

Prerequisites: Math 20A, Math 20B and Math 20F, or consent of the instructor.

• Homework (25%): assigned after each lecture (before 3p), and they will typically be due at the start of the next lecture. The goal of the homework is allow you explore the lecture topics in more detail than allowed in class and to prepare you for lecture discussion. Late assignments are not accepted. As there are 20 lectures, there will be roughly be 20 homework assignments.  In aggregate, these will require as much work as the homework in other courses. The lowest grade lowest two grades will be dropped when computing the final homework score.
• Projects (25%):  There will be a handful of smaller projects that tie together concepts throughout the quarter.
• Midterm exam(25%) - Thursday, November 8th in class
• Final exam (25%) - Thursday, December 13th 3-6pm
  

• Submission: Submission details and format vary by assignment.  Be sure to read details with each assignment.
  
• Lateness: late submissions will not be accepted. Submit whatever you have by the assignment deadline; late homeworks will not be graded, and will be given a zero. I will only make exceptions for medical or family concerns; get in touch with me as soon as possible if this is the case.
• Regrades/Appeals:  
• You have the right of appeal for grading on all tests; however, an appeal (except for scoring errors) covers the entire test, and may result in an unfavorable judgment on another problem. You have one week from the time the midterms are returned to make appeals, including addition errors on your score. Check it over carefully when you get it.
• There is no appeal on homeworks, except for addition errors. No single problem will have a significant impact on your grade.
• I will drop the lowest homework score when calculating your grade.
• Cooperation: All homeworks, projects, and exams in this course are intended to be done by yourself, and with the help of the textbook, teaching assistants, the instructor. You're allowed to discuss problems with classmates, but only in general terms, and you must specifically avoid discussing any solutions.  
• Integrity*: Cheating is taken seriously. It is not fair to honest students to take cheating lightly, nor is it fair to the cheater to let him/her go on thinking that is a reasonable alternative in life.
• What we do NOT consider cheating: Discussing assignments in groups (with the writeup done separately, later) is not considered cheating.
• What we do consider cheating: Discussing assignments with someone who has already completed the problem, or looking at their completed write-up, finding hw solutions on the web or anywhere else. Receiving, providing, or soliciting assistance from another student during a test. Any one homework is not intended to be a grade-maker, but to prepare you for the tests, which are the grade-makers. Cheating on the homeworks is just stupid.
• Penalties - anyone copying information or having information copied during a test will receive an F for the class and will not be allowed to drop. They will be reported to their college dean. If you can prove non-cooperative copying took place, your grade may be restored, but you must prove it to the dean -- I don't want to be involved. 
• Anyone caught cheating on the homework will not be allowed to turn in further homework. Your grade will be based exclusively on the tests and projects (with a suitable penalty applied).
• If you have any questions, ask the instructor immediately.
  
  You must also resist the urge to copy material for assignments from the web. Obviously, there are many Statistics courses and there are likely to be similar approaches elsewhere. While I obviously can't forbid you to look at other slides or text material, any evidence of plagiarism from other sources will merit similar consequences.
  
  You would be amazed how easy it is to detect plagiarism these days, so I must reiterative this policy: All homeworks, projects, and exams in this course are intended to be done by yourself.