• Class Number 1707
• Term Code 2920
• Class Info
• Unit Value 6 units
• Mode of Delivery In Person
• COURSE CONVENER
• Dr Le Chang
• LECTURER
• Dr Le Chang
• Class Dates
• Class Start Date 13/01/2019
• Class End Date 15/03/2019
• Census Date 01/02/2019
• Last Date to Enrol 18/01/2019
SELT Survey Results

Principles of Mathematical Statistics (STAT6039)

A first course in mathematical statistics with emphasis on applications; probability, random variables, moment generating functions and correlation, sampling distributions, estimation of parameters by the methods of moments and maximum likelihood, hypothesis testing, the central limit theorem, simple linear regression.

## Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

1. Use and calculate probability including combinatorics
2. Use and describe discrete, continuous and multivariate random variables and their probability distributions
3. Define sampling distributions and use the central limit theorem
4. Use the method of moments and maximum likelihood estimation
5. Perform confidence estimation and hypothesis testing
6. Use and describe the fundamental concepts of Bayesian statistics and Bayesian estimators

## Research-Led Teaching

This course elaborates as well as builds upon the statistical principles to which you have been exposed in introductory statistics courses. The contents and activities in this course are designed to help you to build a mathematical foundation towards a better understanding of statistical methods and proper handling of data . Course contents and activities may involve some statistical computing with R interfaced through R Studio. R-codes will not be assessed.

• Optional purchase of a hard copy of the course text /or solutions
• Optional purchase of a non-programmable calculator

## Examination Material or equipment

Details of the final assignment will be announced on Wattle.

## Required Resources

Prescribed text and solutions manual (recommended but not compulsory):

• Wackerly, D.D., Mendenhall III, W., and Scheaffer, R.L. (2008). Mathematical Statistics with Applications, Seventh edition. Duxbury, Thomson, Brooks/Cole.
• Owen, W.J. (2008). Student Solutions Manual for Wackerly, Mendenhall, and Scheaffer’s Mathematical Statistics with Applications, Seventh Edition. Duxbury, Thomson, Brooks/Cole.

## Staff Feedback

Feedback from the teaching staff will aim to facilitate the learner's ongoing self assessment of his/her progress in achieving the learning objectives of the course. To this end, the learner should converse with the teaching staff through Wattle’s forum or emails during non-intensive weeks, and in-person during the intensive week. Limited written comments will also be provided through the grading of formal assessments. Note that in order to safeguard student privacy, staff members need to be sure that they are dealing with the right student, therefore course- related messages sent from non-ANU email accounts will be ignored.

## Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.

## Other Information

Any student identified, either during the current semester or in retrospect, as having used ghost writing services will be investigated under the University’s Academic Misconduct Rule.

## Class Schedule

Week/Session Summary of Activities Assessment
1 Pre-intensive period (Jan 13- Feb 10): Probability including combinatorics and Bayes’ theorem Discrete random variables and their probability distributions Continuous random variables and their probability distributions Multivariate random variables and their probability distributions Assignment 1 due
2 Intensive period (Feb 11 - Feb 15): Functions of random variables Sampling distributions and the central limit theorem Methods for point estimation: the method of moments and maximum likelihood estimation Confidence estimation
3 Post-intensive period (Feb 16 - Mar 15): Hypothesis testing Assignment 2 due Final Assignment

## Tutorial Registration

Tutorial registration is not required

## Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Assignment 1 (Turnitin) 20 % 08/02/2019 22/02/2018 Learning Outcomes 1,2 and 6
Assignment 2 (Turnitin) 20 % 14/03/2019 28/03/2018 Learning Outcomes 3, 4 and 5
Final assignment (Turnitin) 60 % 15/03/2019 28/03/2018 Learning Outcomes 1~6

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details

## Policies

ANU has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Misconduct Rule before the commencement of their course. Other key policies and guidelines include:

## Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the ANU Online website. Students may choose not to submit assessment items through Turnitin. In this instance you will be required to submit, alongside the assessment item itself, hard copies of all references included in the assessment item.

## Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.

## Participation

Students will be required to be on campus in Canberra during the one-week intensive period.

## Examination(s)

Any student identified, either during the current semester or in retrospect, as having used ghost writing services will be investigated under the University’s Academic Misconduct Rule.

Value: 20 %
Due Date: 08/02/2019
Return of Assessment: 22/02/2018
Learning Outcomes: Learning Outcomes 1,2 and 6

Assignment 1 (Turnitin)

The assignment will be released two weeks before the due date.

Due date: 2019-02-08 Friday, 3:00 pm Canberra Time

Value: 20%

Value: 20 %
Due Date: 14/03/2019
Return of Assessment: 28/03/2018
Learning Outcomes: Learning Outcomes 3, 4 and 5

Assignment 2 (Turnitin)

The assignment will be released two weeks before the due date.

Due date: 2019-03-14 Thursday, 3:00 pm Canberra Time

Value: 20%

Value: 60 %
Due Date: 15/03/2019
Return of Assessment: 28/03/2018
Learning Outcomes: Learning Outcomes 1~6

Final assignment (Turnitin)

Details of the final assignment will be announced on Wattle.

Due date: 2019-03-15

Value: 60%

## Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.

Each assignment and the final exam must be submitted as a single electronic file using Turnitin within the course Wattle site. If submitting handwritten mathematical derivations, ensure that your handwriting is legible, and scan the derivations (e.g., by using your smartphone camera) to be incorporated into your single electronic file. Prior to submission, you should practice using the Turnitin system here. Students can upload draft versions to the designated Turnitin web link on the Wattle course page, and change those drafts every 24 hours up until the due date.

Submissions outside of the designated Turnitin web link and/or after the due date will be ignored.

## Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

## Late Submission

No submission of assessment tasks without an extension after the due date will be permitted. If an assessment task is not submitted by the due date, a mark of 0 will be awarded.

## Referencing Requirements

Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.

## Returning Assignments

Graded assignments should be available via Turnitin within 14 days after the due date.

## Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. The Course Convener may grant extensions for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

## Resubmission of Assignments

Resubmission of assessments is not allowed under any circumstance.

## Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

## Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

## Convener

 Dr Le Chang 6125 5116 le.chang@anu.edu.au

### Research Interests

Model selection, robust statistics, high-dimensional data analysis, lasso, PCA, spatio-temporal.

### Dr Le Chang

 Monday 00:00 00:00

## Instructor

 Dr Le Chang 6125 5116 le.chang@anu.edu.au

### Dr Le Chang

 Monday 00:00 00:00