Statistical Methods for Data Science (DATA7202)

Course overview

This course will provide students with essential ideas and tools for analysing and interpreting data, including statistical modelling techniques: Linear models, generalised linear models, and regularisation. Students will also be introduced to a range of specific data science tools such as Bayesian techniques and process simulation.

This course will cover linear models and generalized linear models, time series analysis, model selection, dimension reduction, and process simulation withﾠsmall and large datasets. Students will learn theoretical and practical aspects of methods. The assessment tasks include mathematical derivations, statistical analysis, programming, data wrangling, and report writing.

In the School of Mathematics and Physics we are committed to creating an inclusive and empowering learning environment for all students. We value and respect the diverse range of experiences our students bring to their education, and we believe that this diversity is crucial for fostering a rich culture of knowledge sharing and meaningful exploration. We hold both students and staff accountable for actively contributing to the establishment of a respectful and supportive learning environment.

Bullying, harassment, and discrimination in any form are strictly against our principles and against UQ Policy, and will not be tolerated. We have developed a suite of resources to assist you in recognising, reporting, and addressing such behaviour. If you have any concerns about your experience in this course, we encourage you to tell a member of the course teaching team, or alternatively contact an SMP Classroom Inclusivity Champion (see Blackboard for contact details). Our Inclusivity Champions are here to listen, to understand your concerns, and to explore potential actions that can be taken to resolve them. Your well-being and a positive learning atmosphere are of utmost importance to us.

Course requirements

Assumed background

It is assumed that students will have passedﾠ DATA7001 and STAT7203 (or equivalents) prior to enrolling in this course. They should have some ability with R and Python and some programming skills. They will additionally need substantial statistical and mathematical knowledge, as available from the pre-requistes, MATH7052 (& hence also MATH7051) and STAT7203.

Prerequisites

You'll need to complete the following courses before enrolling in this one:

STAT7203 (or STAT2203), MATH7502.

Restrictions

Restricted to MDataSc students only.

Course contact

Course staff

Timetable

The timetable for this course is available on the UQ Public Timetable.

Additional timetable information

All lectures and practicals will be conducted in person. Students are expected to attend these sessions in person unless they have a valid reason for being unable to attend (such as illness). Relevant Zoom links for online activities will be provided on Blackboard. Alternative arrangements will be advised on Blackboard should the campus be closed for any reason.

Important: if you are ill, then do not attend any classes in person. Alternative arrangements can be organised – consult Blackboard for details. Students whose practical falls on a public holiday are invited to attend one of the other practicals for that week.

Aims and outcomes

Students will understand linear models and related methods and be able to apply them using statistical software and report on the results in written and oral forms to assist in decision making. They will learn to generate sample data through simulation to help examine scenarios and test methods. Students will learn to make appropriate decisions about what analyses to undertake and be aware of the advantages and limitations of each method.

Learning outcomes

After successfully completing this course you should be able to:

Assessment

Assessment summary

Assessment details

Assignment 1

Mode

Written

Category

Project

Weight

25%

Due date

31/03/2025 4:00 pm

Learning outcomes

L01, L02, L03, L04, L05, L06

Task description

Submission guidelines

Submit the assignment via the Blackboard Assignment tool.

Deferral or extension

You may be able to apply for an extension.

The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.

See ADDITIONAL ASSESSMENT INFORMATION for extension/deferral information relating to this assessment item.

Late submission

A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.

Assignment 2

Mode

Written

Category

Project

Weight

25%

Due date

30/04/2025 4:00 pm

Learning outcomes

L01, L02, L03, L04, L05, L06

Task description

Submission guidelines

Submit the assignment via the Blackboard Assignment tool.

Deferral or extension

You may be able to apply for an extension.

The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.

See ADDITIONAL ASSESSMENT INFORMATION for extension/deferral information relating to this assessment item.

Late submission

A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.

Assignment 3

Mode

Written

Category

Project

Weight

25%

Due date

28/05/2025 4:00 pm

Learning outcomes

L01, L02, L03, L04, L05, L06

Task description

Submission guidelines

Submit the assignment via the Blackboard Assignment tool.

Deferral or extension

You may be able to apply for an extension.

The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.

See ADDITIONAL ASSESSMENT INFORMATION for extension/deferral information relating to this assessment item.

Late submission

A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.

Exam

• Identity Verified
• In-person

Mode

Written

Category

Examination

Weight

25%

Due date

End of Semester Exam Period

7/06/2025 - 21/06/2025

Other conditions

Time limited.

See the conditions definitions

Learning outcomes

L01, L02, L05, L06

Task description

Exam details

Submission guidelines

Deferral or extension

You may be able to defer this exam.

See ADDITIONAL ASSESSMENT INFORMATION for extension/deferral information relating to this assessment item.

Course grading

Full criteria for each grade is available in the Assessment Procedure.

Supplementary assessment

Supplementary assessment is available for this course.

Should you fail a course with a grade of 3, you may be eligible for supplementary assessment. Refer to my.UQ for information on supplementary assessment and how to apply. 

Supplementary assessment provides an additional opportunity to demonstrate you have achieved all the required learning outcomes for a course.  

If you apply and are granted supplementary assessment, the type of supplementary assessment set will consider which learning outcome(s) have not been met.  

Supplementary assessment in this course will be in the same style as the end-of-semester examination. To receive a passing grade of 3S4, you must obtain a mark of 50% or more on the supplementary assessment.  

Additional assessment information

Artificial Intelligence

Assessment tasks in this course evaluate students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI) or Machine Translation (MT). Students are advised that the use of AI or MT technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.

Applications for Extensions to Assessment Due Dates

Extension requests are submitted online via my.UQ – applying for an extension. Extension requests received in any other way will not be approved. Additional details associated with extension requests, including acceptable and unacceptable reasons, may be found at my.UQ.

Please note:

• Requests for an extension to an assessment due date must be submitted through your my.UQ portal and you must provide documentation of your circumstances, as soon as it becomes evident that an extension is needed. Your application must be submitted on or before the assessment item's due date and time.
• Applications for extension can take time to be processed so you should continue to work on your assessment item while awaiting a decision. We recommend that you submit any completed work by the due date, and this will be marked if your application is not approved. Should your application be approved, then you will be able to resubmit by the agreed revised due date.
• If an extension is approved, you will be notified via your my.UQ portal and the new date and time for submission provided. It is important that you check the revised date as it may differ from the date that you requested.
• If the basis of the application is a medical condition, applications should be accompanied by a medical certificate dated prior to the assignment due date. If you are unable to provide documentation to support your application by the due date and time you must still submit your application on time and attach a written statement (Word document) outlining why you cannot provide the documentation. You must then upload the documentation to the portal within 24 hours.
• If an extension is being sought on the basis of exceptional circumstances, it must be accompanied by supporting documentation (eg. Statutory declaration).
• For extensions based on a SAP you may be granted a maximum of 7 days (if no earlier maximum date applies). See the Extension or Deferral availability section of each assessment for details. Your SAP is all that is required as documentation to support your application. However, additional extension requests for the assessment item will require the submission of additional supporting documentation e.g., a medical certificate. All extension requests must be received by the assessment due date and time.
• Students may be asked to submit evidence of work completed to date. Lack of adequate progress on your assessment item may result in an extension being denied.
• If you have been ill or unable to attend class for more than 14 days, you are advised to carefully consider whether you are capable of successfully completing your courses this semester. You might be eligible to withdraw without academic penalty - seek advice from the Faculty that administers your program.
• There are no provisions for exemption from an assessment item within UQ rules. If you are unable to submit an assessment piece then, under special circumstances, you may be granted an exemption, but may be required to submit alternative assessment to ensure all learning outcomes are met.

Learning resources

You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.

Library resources

Find the required and recommended resources for this course on the UQ Library website.

Learning activities

The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.

Policies and procedures

University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:

• Student Code of Conduct Policy
• Student Integrity and Misconduct Policy and Procedure
• Assessment Procedure
• Examinations Procedure
• Reasonable Adjustments - Students Policy and Procedure

Learn more about UQ policies on my.UQ and the Policy and Procedure Library.