| Instructor: |
Marina Meila Padelford B-321, Box 354322 543-8484 (in Padelford) mmp@{cs.washington.edu,stat.washington.edu} |
| Office hours: | Instructor: Monday 2:10-3 onZoom, TA: TBA |
| TA: | Shreya Prakash NetId: shreyap1 |
| Lecture place and time: | Tue, Thu 12:30-2:20 EE 125
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| Course home page: | http://www.stat.washington.edu/courses/391/spring25.
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| Class mailing list: | multi_stat391a_sp25 |
| Textbooks: |
The textbook for this course is "Probability and Statistics for Computer Science" by Marina Meila, which will be made available for download. Additional course notes will available for download.
Other recommended books are listed on the books web page.
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| Format: | The course will
consist of two weekly 2 hour lectures and weekly homework
assignments. Occasionally, the 4th lecture hour on Thursday will be devoted to special topics, on which you will not be tested (except possibly for extra credit). Lectures will in person, and not recorded. The instructor and TA reserve the right to assign seating during lectures, quizzes and exams. In particular, during lectures, we require everybody present in the EE 105 classroom to sit in the first K rows (K to be determined) during lectures; no exceptions will be made. For quizzes and exams, we will assign seating spread over the whole classroom. Slides will be posted on the handouts/Course notes page ahead of the class; during lectures I will use these slides as background, plus a virtual whiteboard, with GoodNotes. After class, the annotated slides will be posted on Canvas (go to Files/lecture notes). |
| Participation: | Attendance is not mandatory. However,
class participation is important and therefore it will be part of your grade. By class participation I mean more than just being
in class; you're expected to actively participate, either by asking
questions (the easiest) or by answering my questions and my invitations
to comments. Bonus participation points for selected answers on the discussion board may be awarded.
This year for the second time, we will try the following in-class exercises, which will count for participation. Occasionally, we will hand out a sheet of paper with short exercises and questions. You will have 5-10 minutes to work on them. At the end of this period, you can hand in your work or not. If you hand it in, there are the following benefits: you get feedback on it, AND it is equivalent to answering or asking a question in class, hence it adds to your participation points. It does not matter if you were correct or not in your answers, since this work is counted for participation only. How much participation is enough? Once a week on average is plenty. |
| Assignments: | Typically
assignments will be posted on the web (usually) on
Wednesdays and will be due by 5 pm (usually) the following Wednesday. The homework should be submitted as a single pdf file. We do not grade homework answers that are in the code.
The homeworks will consist of problems and short programming assignments. It is important to turn in your homework timely. First, because homework is a component of learning the new material. New lectures will build on past lectures as well as past homework results. Second, fair grading requires fair conditions for everybody. You are allowed to be late with your homework twice with no penalty. Further late homework will be penalized by up to 50%. No late homeworks are accepted once the solutions are out or the graded homework returned (this happens typically one week after the homework due date). Programming assignments:A typical programming assignment is: generate some data from a given distribution, do some processing, plot the results, draw conclusions. You will have to implement the data generation and processing. The programming language is your choice, and you are free (and encouraged!) to use library functions, but you have to write the code for the algorithms that are the subject of the course. For example, you are not expected to implement your own random number generator, but you will have to write code (that will use the random numbers) to simulate a dice roll. You will implement the formula for mean and standard deviation even if the software you are using has a built-in function for that. Occasionally, you may be required to submit the code you used for the programming assignments. This should not be in the same file with the homework, but submitted separately. We will not grade or debug your code, but we will do random checks to see if the code indeed does what it's supposed to do.
Python and Matlab. We will offer some support for those of
you who want to learn one of these languages while taking 391. The TA
will offer a pyton tutorial, and a short intro to Matlab plotting will be
posted. Matlab is very easy to learn on your own, and is awesome at
making plots; however it is not available for free. Python is very popular overall, and also very easy to
learn. Making plots is comparatively less easy, but the package
matplotlib (which emulates the Matlab plotting capabilities) is some help.
Other homework problems will require calculus and easy arithmetic (in addition to what you learn in this class, of course). Both literal and numeric answers should be brought to their simplest form for full credit, and to allow you to fully appreciate the result. Math topics you should review: set theory, combinatorics and counting, taking derivatives and their meaning , integration (integration by parts, elementary properties of integration, primitives of common functions), elementary multivariate calculus and matrix operations. If there is need, tutorial sessions can be arranged for any of these topics.
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| Teamwork: | Students are encouraged to talk to each other, to the TA, to the instructors, or to anyone else about any of the assignments. Any assistance, though, must be limited to discussion of the problem and sketching general approaches to a solution. Each student must write out her or his own solutions to the homework, including the code. We may use plagiarism detection software. Discussion board do's and don'ts: It is okay to ask clarifications about a homework question; i.e. "what does the question mean?" on the discussion board. It is not okay to ask "how do I solve this question?". For example, often we see "what number do I plug into formula (5) to solve Problem 1, a?". Both asking and answering such a question is inappropriate collaboration. |
| Regrading: | If you have reason to believe your homework was not graded correctly, please bring it up with the TA no later than a week after the homework grade is posted. |
| Exam(s) and quizzes: | Exam(s) and quizzes will be all in person in EE 105. No electronics of any kind are allowed; you are required to remove all electronics and deposit them in your bag or on the floor next to your seat. Failure to remove all electronics will be considered cheating and will be treated according to the UW rules. |
| Grading: | The grade in STAT 391 this spring will be 5-10% participation, 40-50% homework, 10-15% quizzes and 25-35% final exam. I am considering also having an optional oral exam (Details will be decided later, depending on the interest for this exam.) Updates 6/1/2025: there will be no oral exam. Grade calculation: 8% participation, 50% homework, 12% quiz, 30% final exam. Dropping policy: you are allowed to drop either a quiz or a homework. Practically, we will compute the grade as max { grade after dropping the quiz with lowest percentage, grade after dropping the homework with lowest percentage } (unless you did perfectly, it is always to your advantage to drop one). |
| Prerequisites: | A class in multivariate calculus (partial derivatives, multiple integrals, matrix algebra). A class in probability, including conditional probability and independence. Ability to write simple programs in order to do the homework. Ability to reason mathematically, to read, understand and discover proofs. Here is a list of the calculus topics we typically use. |