Welcome to the Semester 1, 2017 STAT2201 course, taught at the University of Queensland. The course coordinator and lecturer is Yoni Nazarathy. The second lecturer is Melanie Robertson-Dean. The super-tutor is Hayden Klok. 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. The course has been restructured for 2017 and onwards. For reference, you may look at material from last year's course, but please keep in mind that there are substantial differences.

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.

Some pages from the Facebook history book indicate that in previous years the course was tagged as "Arguably, the most boring course at UQ". Then as the current course coordinator took over (in 2016), that prestigious title was even augmented with "..., and unarguably the most disorganized course.". We did our best to take that feedback on-board. This year the course has changed! Welcome to the new course: More organized (than last year), requiring more thought, requiring less memorisation of technique, involving the cool Julia programming language, integrating concepts of probability, having a bit less in-class assessment but having more out-of-class assessment. Arguably this is not boring. Unarguably it covers concepts and techniques that you will use again and again in your professional career as an engineer.

** 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 (uq.juliabox.com), 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 65% for your final grade. You must pass the exam to receive a passing grade. 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 35% for the final grade and is based on your top 5 assignments. Hence effectively each assignment is worth 7% 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 (uq.juliabox.com). 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.

- Detailed course schedule. (includes schedule and assessment summary)
- Official UQ course profile (see 2017 profile for assesment information).
- UQ Blackboard site with messages and material (requires login)

- Recommended book: Applied Statistics and Probability for Engineers" by D. C. Montgomery and G. C. Runger, available also at Co-op book store, [MonRun2014].
- Condensed course notes.
- Statistics with Julia, STAT2201 Reference Sheet.
- Julia Box (uq.juliabox.com). This is a version of JuliaBox tailored for STAT2201.
- Markdown cheatsheet. Can help with Markdown in JuliaBox, but not mandetory for the course.

- Unit 1 -
*Introduction*- See Unit 1 in Condensed Lecture Notes.

- Unit 2 -
*Probability and Monte Carlo*

- Unit 3 -
*Distributions*

- Unit 4 -
*Joint Distributions*

- Unit 5 -
*Descriptive Statistics*- See lecture 5 above.

- Unit 6 -
*Statistical Inference Ideas*- Lecture 6.
- Wolfram Demo - Illustrating the Central Limit Theorem with Sums of Uniform and Exponential Random Variables.
- Wolfram Demo - Confidence Intervals for a Mean.
- Wolfram Demo - Statistical Power.
- Quiz from previous year (with solution) dealing with simple hypothesis testing, type I error and type II error.

- Unit 7 -
*Single Sample Inference*

- Unit 8 -
*Two Sample Inference*

- Unit 9 -
*Linear Regression*- Wolfram Demo - Least Squares Regression Line.
- Wolfram Demo - Regression Confidence and Prediction Bands.

- Unit 10 -
*What more is there*- Lecture 9.
- Fugro Roames Guest Speakers: Chris Foster and Paul Bellette.
- ANOVA Summary (a simple summary of ANOVA - not examinable).
- ANOVA demonstration in "Seeing Theory".

Submission Instruction Guidelines.

- Assignment 1

- Assignment 2

- Assignment 3
- Assignment 3.
- Data files (csv): BrisGCtemp.csv, Pumps.csv, Fertilizer.csv, 6-42.csv, 6-122.csv.
- Solution 3.

- Assignment 4
- Assignment 4.
- Data files (csv): class4_2.csv, class4_3.csv, 9-65.csv.
- Solution 4.

- Assignment 5
- Assignment 5.
- Solution 5, with thanks to Vincent Mellor.

- Assignment 6
- Assignment 6.
- Data files (csv): 11-6.csv, 11-13.csv, 11-22.csv
- Solution 6, with thanks to Vincent Mellor.

- Formula and Tables Booklet - supplied to students in the exam.
- Exam Example 1, Solution for Exam Example 1.
- Exam Example 2, Solution for Exam Example 2.
- You may look at last year's course for 2 exam examples. Note that material somewhat differs, but the exam nature is similar.