Students

STAT6180 – Applied Statistics

2023 – Session 2, In person-scheduled-weekday, North Ryde

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Convenor
Iris Jiang
iris.jiang@mq.edu.au
Convenor
Thomas Fung
thomas.fung@mq.edu.au
Lecturer
Nan Zou
nan.zou@mq.edu.au
Credit points Credit points
10
Prerequisites Prerequisites
Admission to MAppStat or GradCertAppStat or GradDipAppStat or MSc or MDataSc or MLabQAMgt or GradDipLabQAMgt or GradCertLabQAMgt or MScInnovationStat
Corequisites Corequisites
STAT6170 or STAT670
Co-badged status Co-badged status
STAT2170
Unit description Unit description

This unit aims to extend and broaden statistical experience from STAT6170, with a focus on application to real-world analysis. It covers 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. Data management, report writing, graphical presentation of results, and power analysis are described.

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: Summarise data graphically and numerically and interpret them.
  • ULO2: Apply appropriate statistical methods, such as one-way ANOVA, two-way ANOVA and multiple regression, to answer research questions.
  • ULO3: Understand and evaluate the assumptions underlying the models, and modify the analysis if needed.
  • ULO4: Use statistical software to create model output and interpret them.

Assessment Tasks

Name Weighting Hurdle Due
iLearn Quiz 20% No Week 4
Mid-Semester Test 25% No Week 7
Assignment 25% No Week 11
Final Exam 30% No Formal Examination Period

iLearn Quiz

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 1 hours
Due: Week 4
Weighting: 20%

 

The quiz will become available on iLearn.

 
On successful completion you will be able to:
  • Summarise data graphically and numerically and interpret them.
  • Apply appropriate statistical methods, such as one-way ANOVA, two-way ANOVA and multiple regression, to answer research questions.
  • Understand and evaluate the assumptions underlying the models, and modify the analysis if needed.
  • Use statistical software to create model output and interpret them.

Mid-Semester Test

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 1 hours
Due: Week 7
Weighting: 25%

 

Mid-semester Test

 
On successful completion you will be able to:
  • Summarise data graphically and numerically and interpret them.
  • Apply appropriate statistical methods, such as one-way ANOVA, two-way ANOVA and multiple regression, to answer research questions.
  • Understand and evaluate the assumptions underlying the models, and modify the analysis if needed.
  • Use statistical software to create model output and interpret them.

Assignment

Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 10 hours
Due: Week 11
Weighting: 25%

 

The assignment will cover all learning outcomes.

 
On successful completion you will be able to:
  • Summarise data graphically and numerically and interpret them.
  • Apply appropriate statistical methods, such as one-way ANOVA, two-way ANOVA and multiple regression, to answer research questions.
  • Understand and evaluate the assumptions underlying the models, and modify the analysis if needed.
  • Use statistical software to create model output and interpret them.

Final Exam

Assessment Type 1: Examination
Indicative Time on Task 2: 2 hours
Due: Formal Examination Period
Weighting: 30%

 

Formal invigilated examination testing the learning outcomes of the unit.

 
On successful completion you will be able to:
  • Summarise data graphically and numerically and interpret them.
  • Apply appropriate statistical methods, such as one-way ANOVA, two-way ANOVA and multiple regression, to answer research questions.
  • Understand and evaluate the assumptions underlying the models, and modify the analysis if needed.
  • Use statistical software to create model output and interpret them.

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

Lectures (beginning in Week 1): There is one two-hour lectures each week.

SGTA classes (beginning in Week 2): Students must register in and attend one two-hour class per week.

The timetable for classes can be found on the University website at: https://timetables.mq.edu.au/

Enrolment can be managed using eStudent at: https://students.mq.edu.au/support/technology/systems/estudent

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:

Communication

We will communicate with you via your university email or through announcements on iLearn. Queries to convenors can either be placed on the iLearn discussion forum or sent to your lecturers from your university email address.

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 Assignment
1 Course introduction; One-sided tests; Type I and Type II error; Introduction to R/RStudio  
2 Modified two-sample t-test; Assessing normality and equal variance assumptions  
3 One way ANOVA  
4 One way ANOVA, Multiple comparisons  iLearn Quizzes Due
5 Transformations; Non-parametrics; Power and Sample Size  
6 Data management; R Markdown; Simple linear regression  
7 Simple linear regression and model validation; Multiple regression Mid-Semester Test Due
Session 2 Break    
8 Multiple regression and model validation  
9 Extensions and examples of multiple regression  
10 Two-way ANOVA  
11 Two-Way ANOVA and Multiple Comparisons Assignment Due
12 Two-Way ANOVA, Regression and Multiple Comparisons  
13 Exam Details and Revision  

 

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 ask.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 AskMQ, 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

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.

Based on valuable student feedback gathered through student representatives and surveys, we have taken proactive steps to enhance the student learning experience. In response to concerns about bloated lecture materials, we have made targeted revisions to streamline the content, ensuring a more focused and efficient approach to course delivery. These revisions include the removal of redundant or repetitive examples, allowing for a more concise and impactful learning journey for our students. By carefully considering the feedback received, we aim to create an optimised learning environment that maximizes student engagement and facilitates a deeper understanding of the subject matter.

Hurdle Assessments

There is no Hurdle Assessment.

Late Assessment Submission Penalty

Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark) will be applied each day a written 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. Submission time for all written assessments is set at 11:55 pm. A 1-hour grace period is 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, students need to submit an application for Special Consideration.

Assessments where Late Submissions will be accepted.

  • iLearn Quiz – NO, unless Special Consideration is granted;
  • Mid-Semester Test – NO, unless Special Consideration is granted;
  • Assignment – YES, Standard Late Penalty applies;
  • Final Exam – NO, unless Special Consideration is granted.

Requirements to Pass this Unit

To pass this unit you must:

  • Achieve a total mark equal to or greater than 50%.

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.

Written Assessments/Quizzes/Tests: If you experience circumstances or events that affect your ability to complete the written assessments in this unit on time, please inform the convenor and submit a Special Consideration request through ask.mq.edu.au.

Unit information based on version 2023.02 of the Handbook