Students

STAT6190 – Statistical Methods for Data Science

2025 – Session 1, In person-scheduled-weekday, North Ryde

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff
Maurizio Manuguerra
maurizio.manuguerra@mq.edu.au
Credit points Credit points
10
Prerequisites Prerequisites
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description

This unit provides a broad introduction to statistical concepts and data analysis techniques, with a focus on application to real-world analysis and report typesetting skills. With the support of a coding language for statistical computing and graphics like R, students will learn about data collection and summarisation, basic probability, random variables, statistical models like the normal distribution, sampling distributions and statistical inferences about means and proportions. Students will then learn how to model the relationships between categorical or continuous explanatory variables and a continuous response variable using the techniques of one-way and two-way analysis of variance and simple and multiple linear regression. 

Learning in this unit enhances student understanding of global challenges identified by the United Nations Sustainable Development Goals (UNSDGs) Industry, Innovation and Infrastructure

 

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • ULO1: Create, assess, and interpret numerical and visual summaries for various data types, including extensive or intricate datasets.
  • ULO2: Apply basic concepts of probability, random variables and sampling distributions to solve practical problems.
  • ULO3: Identify, justify and implement appropriate parametric or non-parametric statistical tests.
  • ULO4: Formulate, validate, evaluate and interpret appropriate linear models to describe the correlations among multiple factors.
  • ULO5: Create a reproducible report to communicate statistical insights using a literate programming tool.
  • ULO6: Create specific questions tailored to the context or domain and determine the suitable statistical methods for analysis.

General Assessment Information

Requirements to Pass this Unit

To pass this unit you must achieve a total mark equal to or greater than 50%.

To enable students more time to focus on learning, understanding and reflecting on the content of our unit we have designed the assessment structure as follows. There are now only two assessments: a mid-session exam (the Problem Set) and the final assignment (the Case Study). Although no marks are associated with attendance, all activities provide you with key content designed to help you complete the assessments. Therefore, we strongly encourage all students to actively participate in all learning activities. Regular engagement is crucial for your success in this unit, as these activities directly prepare you for the assessment tasks, provide opportunities to solve assessment-like questions, deepen your understanding of the material, collaborate with peers, and receive valuable feedback from instructors. Your active participation not only enhances your own learning experience but also contributes to a vibrant and dynamic learning environment for everyone.

Late Assessment Submission Penalty

Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark of the task) will be applied for each day a written report or presentation assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a grade of ‘0’ will be awarded even if the assessment is submitted. The submission time for all uploaded assessments is 11:55 pm. A 1-hour grace period will be provided to students who experience a technical concern. For any late submission of time-sensitive tasks, such as scheduled tests/exams, performance assessments/presentations, and/or scheduled practical assessments/labs, please apply for Special Consideration.

Assessments where Late Submissions will be accepted.

  • Problem set – NO, unless Special Consideration is granted
  • Case study – YES, Standard Late Penalty applies

Special Consideration

The Special Consideration Policy aims to support students who have been impacted by short-term circumstances or events that are serious, unavoidable and significantly disruptive, and which may affect their performance in assessment. If you experience circumstances or events that affect your ability to complete the assessments in this unit on time, please inform the convenor and submit a Special Consideration request through https://connect.mq.edu.au.

Description of Assessment Activities

  • Mid-session exam (Problem Set)
    • Paper-based, i.e., you won't be allowed to use a computer
    • During the SGTA class of week 7
    • Closed-books
    • One 2-sided page of notes allowed (handwritten or typed)
  • Final assignment (Case Study)
    • Due date in the first week of the exam period
    • Submission on iLearn via Turnitin
    • Only PDF files accepted
    • The required format is a report typeset in RMarkdown

Assessment Tasks

Name Weighting Hurdle Due
Problem Set 50% No 07/04/2025
Case study 50% No 15/06/2025

Problem Set

Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 15 hours
Due: 07/04/2025
Weighting: 50%

 

This task will test the ability of students to analyse and solve provided problems.

 
On successful completion you will be able to:
  • Create, assess, and interpret numerical and visual summaries for various data types, including extensive or intricate datasets.
  • Apply basic concepts of probability, random variables and sampling distributions to solve practical problems.
  • Identify, justify and implement appropriate parametric or non-parametric statistical tests.
  • Formulate, validate, evaluate and interpret appropriate linear models to describe the correlations among multiple factors.

Case study

Assessment Type 1: Case study/analysis
Indicative Time on Task 2: 20 hours
Due: 15/06/2025
Weighting: 50%

 

Students are required carry out a case study on a real-world dataset. Students will ultimately communicate their findings in a reproducible report.

 
On successful completion you will be able to:
  • Create, assess, and interpret numerical and visual summaries for various data types, including extensive or intricate datasets.
  • Apply basic concepts of probability, random variables and sampling distributions to solve practical problems.
  • Identify, justify and implement appropriate parametric or non-parametric statistical tests.
  • Formulate, validate, evaluate and interpret appropriate linear models to describe the correlations among multiple factors.
  • Create a reproducible report to communicate statistical insights using a literate programming tool.
  • Create specific questions tailored to the context or domain and determine the suitable statistical methods for analysis.

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • the Writing Centre for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation

Delivery and Resources

Classes

  • Workshops: Students are strongly encouraged to attend one one-hour workshop each week.
  • SGTA classes: Students are strongly encouraged to attend one two-hour class per week.

Students can use the Class Finder tool in eStudent to see when and where the classes are being held and if they have space.  Enrolment can be managed using eStudent at: https://students.mq.edu.au/support/technology/systems/estudent

Week 1 classes

In week one, both workshop and SGTA classes are delivered. Week 1 SGTA class is offered on Monday 24  February, 4pm-6pm. Week 1 workshop is offere on Friday 28 February, 9am-10am.

Suggested textbooks

The following textbook is useful as supplementary resources, for additional questions and explanations. They are available from the Macquarie University library:

  • Moore, D.S., 2017. Introduction to the Practice of Statistics. WH Freeman and company.

Technology Used and Required

This subject requires the use of the following computer software:

Methods of Communication

We will communicate with you via your university email and through announcements on iLearn. Queries to convenors can either be placed on the iLearn discussion board or sent to the unit convenor via the contact email on iLearn.

COVID Information

For the latest information on the University’s response to COVID-19, please refer to the Coron- avirus infection page on the Macquarie website: https://www.mq.edu.au/about/coronavirus-faqs. Remember to check this page regularly in case the information and requirements change during semester. If there are any changes to this unit in relation to COVID, these will be communicated via iLearn.

Unit Schedule

This is a draft schedule and is subjected to change.

Week Topics Assessment
1 Statistical Learning. Research questions, population, samples, data types and summaries; Introduction to R/RStudio  
2 Random variables and distributions; normal distribution, binomial distribution  
3 Statistical inference, sampling distributions and the concept of hypothesis test  
4 Multiple regression: how to write and run a model  
5 Multiple regression: assumptions, transformations and predictions  
6 Parametric and non-parametric hypothesis tests  
7 Analysis of 1 continuous variable: one-sample t-test and Wilcoxon one-sample signed-rank test Mid-Session Exam during SGTA class
Session Break    
8 Analysis of 1 categorical variable: chi-squared goodness of fit test  
9 Analysis of 2 categorical variables: chi-squeared test of independence, Fisher's exact test  
10 Analysis of 1 continuous and 1 categorical variable: two-sample t-test, 1-way ANOVA, Tukey’s HSD, Mann-Whitney U test, Kruskal-Wallis test  
11 Analysis of 1 continuous and 1 categorical variable: two-sample t-test, 1-way ANOVA, Tukey’s HSD, Mann-Whitney U test, Kruskal-Wallis test  
12 Analysis of 1 continuous and 2 categorical variables: 2-way ANOVA  
13 Revision and QA for the final assigment  
14   Assignment Due

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:

Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.

To find other policies relating to Teaching and Learning, visit Policy Central (https://policies.mq.edu.au) and use the search tool.

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct

Results

Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit connect.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

Academic Integrity

At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

The Writing Centre

The Writing Centre provides resources to develop your English language proficiency, academic writing, and communication skills.

The Library provides online and face to face support to help you find and use relevant information resources. 

Student Services and Support

Macquarie University offers a range of Student Support Services including:

Student Enquiries

Got a question? Ask us via the Service Connect Portal, or contact Service Connect.

IT Help

For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/. 

When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.

Changes from Previous Offering

This is the first offering of this unit.

We value student feedback to be able to continually improve the way we offer our units. As such we encourage students to provide constructive feedback via student surveys, to the teaching staff directly, or via the FSE Student Experience & Feedback link in the iLearn page.

Unit information based on version 2025.03 of the Handbook