• Class Number 4424
• Term Code 3130
• Class Info
• Unit Value 6 units
• Mode of Delivery In Person
• COURSE CONVENER
• Dr Yanrong Yang
• LECTURER
• Dr Yanrong Yang
• Class Dates
• Class Start Date 22/02/2021
• Class End Date 28/05/2021
• Census Date 31/03/2021
• Last Date to Enrol 01/03/2021
SELT Survey Results

Statistical Inference (STAT3013)

This course introduces students to the basic theory behind the development and assessment of statistical analysis techniques in the areas of point and interval estimation, as well as hypothesis testing.  Topics include:
* Point estimation methods, including method of moments and maximum likelihood, bias and variance, mean-squared error, sufficiency, completeness, exponential families, the Cramer-Rao inequality, the Rao-Blackwell theorem, uniformly minimum variance unbiased estimators, and Bayesian estimation methods.
* Confidence interval construction methods, including likelihood-based intervals, inversion methods, intervals based on pivots, Bayesian credible and highest posterior density regions, and resampling based intervals.
* Hypothesis testing methods, including likelihood ratio tests, the Neymann-Pearson lemma and uniformly most powerful tests, power calculations, Bayesian approaches, and non-parametric approaches.

## Learning Outcomes

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

1. Explain the notion of a parametric model and point estimation of the parameters of those models;
2. Explain and apply approaches to include a measure of accuracy for estimation procedures and our confidence;
3. Assess the plausibility of pre-specified ideas about the parameters of a model by examining the area of hypothesis testing;
4. Explain and apply non-parametric statistics; and,
5. Discuss the computational issues related to the implementation of various statistical inferences.

## Research-Led Teaching

The topic of statistical inference seeks to provide answers to questions of point estimation, interval estimation and hypothesis testing, based on observable data. Not surprisingly, through the development of this topic over the past couple centuries, there exist diverse approaches to these problems. Examination and application of these diverse approaches will provide insight into the past and potentially future development of statistical science.

The only other additional course costs are textbook (if purchased) and printing materials.

## Examination Material or equipment

Examination material and condition will be noticed to all students via Wattle and the examination office.

G. Casella and R. Berger (2002). Statistical Inference (second edition). Cengage Learning.

Electronic version is available: https://fsalamri.files.wordpress.com/2015/02/casella_berger_statistical_inference1.pdf

G. Givens and J. Hoeting (2013). Computational Statistics. Wiley.

Electronic version is available: http://home.ustc.edu.cn/~liweiyu/documents/Geof%20H.%20Givens%20%20Jennifer%20A.%20Hoeting(auth.)%20-%20Comp.pdf

The lecturer has requested that the ANU library makes the textbook available as a 2 hour or 2 day loan.

The lecturer has requested that the campus bookstore makes the textbook available.

## Staff Feedback

Students will be given feedback in the following forms in this course:

• feedback to whole class, groups, individuals, focus group etc

## 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.

## Class Schedule

Week/Session Summary of Activities Assessment
1 Overview of Statistical Inference and General Information
2 Properties of A Random Sample
3 Principles of Data Reduction Submission of Assignment 1
4 Point Estimation (1): methods of finding estimators Feedback of Assignment 1
5 Point Estimation (2): methods of evaluating estimators
6 Hypothesis Testing (1): methods of finding test statistics
7 Hypothesis Testing (2): methods of evaluating test statistics Submission of Assignment 2
8 Interval Estimation (1): methods of finding interval estimators Feedback of Assignment 2
9 Interval Estimation (2): methods of evaluating interval estimators
10 Asymptotic Evaluations for point estimation, hypothesis tests and interval estimation
11 Robust Estimation: M - Estimation Submission of Assignment 3
12 Analysis of Variance and Regression Feedback of Assignment 3

## Tutorial Registration

Tutorials will be available on campus, live through scheduled zoom sessions, and as pre-recorded videos. Information regarding enrolments for these options will be provided on Wattle during O-Week prior to the start of the semester.

## Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Assignment 1 10 % 12/03/2021 19/03/2021 1,2
Assignment 2 10 % 23/04/2021 30/04/2021 1,2,3
Assignment 3 10 % 21/05/2021 28/05/2021 1,2,3,4,5
Final Exam 70 % 03/06/2021 01/07/2021 1,2,3,4,5

* 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 Academic Integrity . In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

## 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

Course content delivery will take the form of pre-recorded weekly lectures (available via echo360 on Wattle) and weekly tutorials, delivered in hybrid format (on campus, live through scheduled Zoom sessions and as pre-recorded videos).

## 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. Centrally scheduled examinations through Examinations, Graduations & Prizes will be timetabled prior to the examination period. Please check ANU Timetabling for further information.

Value: 10 %
Due Date: 12/03/2021
Return of Assessment: 19/03/2021
Learning Outcomes: 1,2

Assignment 1

Turnitin Submission. The students are expected to complete this assignment individually. This assignment is designed to cover materials from Week 1 and Week 2. Assignment questions consist of calculations and logical analysis. The assignment questions will be released two weeks before the due date. The notification about access to the assignment will also be announced on Wattle in Week 1. Assignments are expected to be in a pdf or word file and contain relevant R codes and graphics. This assignment is not redeemable.

Value: 10 %
Due Date: 23/04/2021
Return of Assessment: 30/04/2021
Learning Outcomes: 1,2,3

Assignment 2

Turnitin Submission. The students are expected to complete this assignment individually. This assignment is designed to cover materials from Week 3 to Week 6. Assignment questions consist of calculations and logical analysis. The assignment questions will be released two weeks before the due date. The notification about access to the assignment will also be announced on Wattle in Week 5. Assignments are expected to be in a pdf or word file and contain relevant R codes and graphics. This assignment is not redeemable.

Value: 10 %
Due Date: 21/05/2021
Return of Assessment: 28/05/2021
Learning Outcomes: 1,2,3,4,5

Assignment 3

Turnitin Submission. The students are expected to complete this assignment individually. This assignment is designed to cover materials from Week 7 to Week 10. Assignment questions consist of calculations and logical analysis. The assignment questions will be released two weeks before the due date. The notification about access to the assignment will also be announced on Wattle in Week 9. Assignments are expected to be in a pdf or word file and contain relevant R codes and graphics. This assignment is not redeemable.

Value: 70 %
Due Date: 03/06/2021
Return of Assessment: 01/07/2021
Learning Outcomes: 1,2,3,4,5

Final Exam

The final exam will be based on all the materials covered throughout the duration of the semester. It is an open book exam and the duration is 4 hours. The final examination is a compulsory piece of assessment and worth 70% of the final raw score. Students will be provided with further details regarding the exam before the end of week 10. The exact date will be made available by the University.

Academic integrity is a core part of the ANU culture as a community of scholars. At its heart, academic integrity is about behaving ethically, committing to honest and responsible scholarly practice and upholding these values with respect and fairness.

The ANU commits to assisting all members of our community to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to be familiar with the academic integrity principle and Academic Misconduct Rule, uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with.

## 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.

## Hardcopy Submission

There is no hardcopy submission in the course.

## Late Submission

No late submission of assessment tasks will be permitted. If an assessment task is not submitted by the due date and time, 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

The marked assignments will be returned online.

## Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted 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

It will not be possible for assignments to be resubmitted.

## 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 Yanrong Yang 02 6125 8975 yanrong.yang@anu.edu.au

### Research Interests

High Dimensional Statistics; Panel Data Analysis; Large Dimensional Random Matrix Theory; Functional Data Analysis

### Dr Yanrong Yang

 Friday 14:00 16:00 Friday 14:00 16:00

## Instructor

 Dr Yanrong Yang 02 6125 8975 yanrong.yang@anu.edu.au

### Dr Yanrong Yang

 Friday 14:00 16:00 Friday 14:00 16:00