Welcome to the Semester 1, 2018 STAT2201 course, taught at the University of Queensland. The course coordinator and lecturer is Dr. Yoni Nazarathy. The second lecturer is Dr. Radislav (Slava) Vaisman. The super-tutor is Dr. Vincent Mellor. Administrative support is given by John Cohen, reached at stat2201@uq.edu.au. Any queries about enrolments, group changes, late submissions or similar should be sent to that address.
STAT2201 is a 1 unit course (a full semester course at UQ is typically 2 units). The majority of the student body includes mechanical, civil, mining, robotics and aerospace engineering students. Note that most of the civil engineering students following the course are enrolled in the (2 unit) CIVL2530 course. For those students, STAT2201 yields part of the CIVL2530 grade.
This year's course is similar to last year's version, hence you may use resources from that year as an aid.
Q: What will I learn? A: You will learn elementary ideas, concepts and methods from data analysis, probability and inferential statistics. You will come out of this course armed with the language of probability and statistics and ready to converse with professionals using these tools and/or dive into further techniques used in the real engineering world.
Q: How does the Julia programming language fit in? A: It is a tool that you will use for data analysis and inferential statistics. You can use it with Julia Box, through any web browser as described in the "Julia basic instructions" below. The world is full of mathematical, scientific and statistical programming languages and Julia is just one example of such a language. Julia is a relative new comer to the scientific programming language community and is well known for striking a remarkable balance between high performance and ease of use. STAT2201 is not a programming course. You will only be required to carry out basic data analysis and Monte Carlo computations using Julia, based on examples presented in the Lectures and Tutorials.
Q: How am I assessed?
A: Your STAT2201 grade is based on the following:
(I) A final exam with a weight of 60% for your final grade. You must get at least 40/100 on the exam to receive a passing grade for the course. The exam duration is 2 hours, giving you ample time to think.
(II) Individual assignments involving analytic computations, data analysis using Julia, essay (understanding). There are 6 assignments in total. Your grade for the assignments carries a weight of 40% for the final grade and is based on your top 5 assignments. Hence effectively each assignment is worth 8% of the grade.
Q: What do I do?
A: Just follow (I) -- (X):
(I) Study the detailed course schedule below and align it with your schedule.
(II) Obtain a copy of the Recommended Book and glance through the book prior to attending lectures.
(III) Attend weekly lectures, bringing a printout of the condensed course notes with you (link below).
(IV) After the lecture, review the concepts taught and attend lecturer visit hours if needing clarification.
(V) Attend weekly tutorials (as scheduled) to start the assignment.
(VI) Continue working on the assignments individually using pen, paper and Julia Box. Hand in on time.
(VII) Review comments on marked assignments and attend lecturer visit hours if needing clarification.
(VIII) Prepare for the final exam by studying the book, the condensed course notes, the 6 assignments and 2 practice exams that will be provided.
(IX) Attend the final exam and use all 2 hours of the exam to think and produce correct answers.
(X) Obtain the highest mark possible.