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Unit of study_

MATH1905: Statistical Thinking with Data (Advanced)

Semester 2, 2023 [Normal day] - Camperdown/Darlington, Sydney

This unit is designed to provide a thorough preparation for further study in mathematics and statistics. It is a core unit of study providing three of the twelve credit points required by the Faculty of Science as well as a foundations requirement in the Faculty of Engineering. This Advanced level unit of study parallels the normal unit MATH1005 but goes more deeply into the subject matter and requires more mathematical sophistication.

Unit details and rules

Unit code MATH1905
Academic unit Mathematics and Statistics Academic Operations
Credit points 3
MATH1005 or MATH1015 or STAT1021 or ECMT1010 or ENVX1001 or ENVX1002 or BUSS1020 or DATA1001 or DATA1901
Assumed knowledge

HSC Mathematics Extension 2 or 90 or above in HSC Mathematics Extension 1 or equivalent

Available to study abroad and exchange students


Teaching staff

Coordinator Linh Nghiem,
Lecturer(s) Linh Nghiem,
Type Description Weight Due Length
Supervised exam
Written and MCQ
60% Formal exam period 1.5 hours
Outcomes assessed: LO4 LO5 LO7 LO6 LO1 LO2 LO3 LO8 LO9
Online task Quiz 1
Written and MCQ
8% Week 04
Due date: 25 Aug 2023 at 23:59

Closing date: 25 Aug 2023
40 minutes
Outcomes assessed: LO1 LO3 LO2
Assignment Assignment 1
Written assignment
5% Week 08
Due date: 22 Sep 2023 at 23:59

Closing date: 03 Oct 2023
2-4 pages (as a guide)
Outcomes assessed: LO1 LO4 LO5 LO6 LO2 LO3
Online task Quiz 2
Written and MCQ
15% Week 11
Due date: 20 Oct 2023 at 23:59

Closing date: 20 Oct 2023
40 minutes
Outcomes assessed: LO4 LO6 LO7 LO5
Assignment Assignment 2
Submitted work
10% Week 13
Due date: 03 Nov 2023 at 23:59

Closing date: 13 Nov 2023
6-8 pages (as a guide)
Outcomes assessed: LO7 LO6 LO8 LO9
Participation Tutorials
Participation in tutorials
2% Weekly 50 minutes/week
Outcomes assessed: LO1 LO9 LO8 LO7 LO6 LO5 LO4 LO3 LO2

Assessment summary

  • Examination: There is one examination during the examination period at the end of Semester 2. Further information about the exam will be made available at a later date on the website. If a second replacement exam is required, this exam may be delivered via an alternative assessment method, such as a viva voce (oral exam). The alternative assessment will meet the same learning outcomes as the original exam. The format of the alternative assessment will be determined by the unit coordinator. 
  • Quizzes: quizzes will be held online through Canvas. The quizzes are 40 minutes and have to be submitted by the closing time of 23:59 on the due date. The quiz can be taken any time during the 24 hour period before the closing time. The better mark principle will be used for the quiz so do not submit an application for Special Consideration or Special Arrangements if you miss a quiz. The better mark principle means that the quiz counts if and only if it is better than or equal to your exam mark. If your quiz mark is less than your exam mark, the exam mark will be used for that portion of your assessment instead.
  • Assignments: There are two assignments, which must be submitted electronically, as PDF files only, in Turnitin, via Canvas by the deadline. Note that your assignment will not be marked if it is illegible or if it is submitted sideways or upside down. It is your responsibility to check that your assignment has been submitted correctly (check that you can view each page). Late submisions will receive a penalty. A mark of zero will be awarded for all submissions more than 10 days past the original due date. Further extensions past this time will not be permitted.
  • Tutorial Participation: This is a satisfactory/non-satisfactory mark assessing whether or not you participate in class activities during the tutorials. It is 0.25 marks per tutorial class up to 8 tutorials (there are 12 tutorials).

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range


High distinction

85 - 100

Representing complete or close to complete mastery of the material.


75 - 84

Representing excellence, but substantially less than complete mastery.


65 - 74

Representing a creditable performance that goes beyond routine knowledge and understanding, but less than excellence.


50 - 64

Representing at least routine knowledge and understanding over a spectrum of topics and
important ideas and concepts in the course.


0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website  provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.  

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Week 01 Introduction, experiment versus observational data Lecture (2 hr) LO1 LO9
Week 02 Descriptive statistics: graphical displays and numerical summaries Lecture (2 hr) LO2 LO9
Week 03 Principles of probabilities Lecture (2 hr) LO3 LO9
Week 04 Discrete random variables Lecture (2 hr) LO3 LO4 LO9
Week 05 Continuous random variables, normal distribution Lecture (2 hr) LO4 LO9
Week 06 Sampling distributions and central limit theorem Lecture (2 hr) LO4 LO5 LO9
Week 07 Point estimation and confidence intervals for normal distribution Lecture (2 hr) LO6 LO9
Week 08 Point estimation and confidence interval for proportion Lecture (2 hr) LO5 LO6 LO9
Week 09 Hypothesis testing concepts, one-sample statistical tests Lecture (2 hr) LO7 LO9
Week 10 Two-sample and chi-square tests Lecture (2 hr) LO3 LO7 LO9
Week 11 Correlation and regression Lecture (2 hr) LO8 LO9
Week 12 Correlation and regression Lecture (2 hr) LO8 LO9
Week 13 Revision Lecture (2 hr) LO1 LO2 LO3 LO8 LO9
Weekly Weekly tutorial Tutorial (1 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9

Attendance and class requirements

Due to the exceptional circumstances caused by the COVID-19 pandemic, attendance requirements for this unit of study have been amended. Where on-campus or online tutorials/workshops/laboratories have been scheduled, students should make every effort to attend and participate at the scheduled time. If you are unable to attend for any reason (e.g. health or technical issues) you should attend another session, if available. Penalties will not apply if you cannot attend your scheduled class.

  • Attendance: Unless otherwise indicated, students are expected to attend a minimum of 80% of timetabled activities for a unit of study, unless granted exemption by the Associate Dean.
  • Tutorial attendance: You should attend the tutorial given on your personal timetable. Attendance at tutorials will be recorded. Your attendance will not be recorded unless you attend the tutorials in which you are enrolled.  While there is no penalty if 80% attendance is not met we strongly recommend you attend tutorials regularly to keep up with the material and to engage with the tutorial questions. Since there is no assessment associated with the tutorials do not submit an application for Special Consideration or Special Arrangements for missed tutorials. Tutorials start in week 2.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 3 credit point unit, this equates to roughly 60-75 hours of student effort in total.

Required readings

  • Textbook: Introductory Statistics (4th. edition), by Sheldon M. Ross (online access via Usyd library)

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. Explain the difference between a randomised controlled experiment and an observational study, in particular the limitations of the latter
  • LO2. Produce and interpret various graphical and numerical summaries of univariate and bivariate data
  • LO3. Solve problems using principles of probabilities
  • LO4. Explain and perform correct computations for some fundamental probability distributions
  • LO5. Explain the concept of sampling distribution and central limit theorem.
  • LO6. Perform appropriate point estimation and confidence interval
  • LO7. Explain the concepts related to hypothesis testing, perform appropriate statistical tests in some simple settings
  • LO8. Determine when and how to use least-squares regression and correlation to describe a bivariate relationship
  • LO9. Apply the methods learnt to various real-world examples and draw sensible, practical statistical conclusions from them

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities

This section outlines changes made to this unit following staff and student reviews.

Minor changes were made to the weightings for quiz 1 and assignment 1. An additional assignment was added and a tutorial participation mark.


The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.