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Unit outline_

MATH1905: Statistical Thinking with Data (Advanced)

Semester 2, 2020 [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 Junior level 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

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 Lamiae Azizi,
Type Description Weight Due Length
Final exam (Open book) Type C final exam Exam
Written and MCQ
70% Formal exam period 1.5 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8
Assignment Quiz 1
5% Week 04
Due date: 17 Sep 2020 at 23:59

Closing date: 17 Sep 2020
40 minutes
Outcomes assessed: LO2 LO3 LO4
Assignment Assignment 1
Written assignment
20% Week 09
Due date: 29 Oct 2020 at 23:59

Closing date: 29 Oct 2020
4-6 pages
Outcomes assessed: LO2 LO3 LO4 LO5 LO6 LO8
Assignment Quiz 2
5% Week 11
Due date: 12 Nov 2020 at 23:59

Closing date: 12 Nov 2020
40 minutes
Outcomes assessed: LO6 LO8
Type C final exam = Type C final exam ?

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.
  • 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 is one assignment, 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.

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 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 Intro/Chapters 1 and 2 Lecture (2 hr) LO1 LO2 LO8
Week 02 Chapters 3 and 4 Lecture (2 hr) LO2 LO8
Tutorial 1 Tutorial (1 hr) LO2 LO8
Week 03 Chapters 5 and 6 Lecture (2 hr) LO2 LO3 LO8
Tutorial 2 Tutorial (1 hr) LO2 LO3 LO8
Week 04 Chapters 8 and 9 Lecture (2 hr) LO2 LO4 LO8
Tutorial 3 Tutorial (1 hr) LO2 LO3 LO4 LO8
Week 05 Chapters 10 and 11 Lecture (2 hr) LO2 LO3 LO4 LO8
Tutorial 4 Tutorial (1 hr) LO2 LO3 LO4 LO8
Week 06 Chapter 12 and geometry of regression Lecture (2 hr) LO2 LO3 LO4 LO8
Tutorial 5 Tutorial (1 hr) LO2 LO3 LO4 LO8
Week 07 Chapter 13, 14, 15 and 16 Lecture (2 hr) LO5 LO6 LO8
Tutorial 6 Tutorial (1 hr) LO5 LO6 LO8
Week 08 Chapters 17 and 18 Lecture (2 hr) LO3 LO5 LO6
Tutorial 7 Tutorial (1 hr) LO3 LO5 LO6
Week 09 Central Limit Theorem Lecture (2 hr) LO3 LO5
Tutorial 8 Tutorial (1 hr) LO3 LO5
Week 10 Chapters 20 and 21 Lecture (2 hr) LO3 LO6
Tutorial 9 Tutorial (1 hr) LO3 LO6
Week 11 Chapters 23 and 26 Lecture (2 hr) LO6 LO7 LO8
Tutorial 10 Tutorial (1 hr) LO6 LO7 LO8
Week 12 Chapters 28 and 29 Lecture (2 hr) LO6 LO7 LO8
Tutorial 11 Tutorial (1 hr) LO6 LO7 LO8

Attendance and class requirements

  • 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: Statistics (4th Edition) – Freedman, Pisani, and Purves (2007)

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. Determine when and how to use the normal curve to approximate frequencies and probabilities
  • LO4. Determine when and how to use least-squares regression and correlation to describe a bivariate relationship
  • LO5. Show mathematically why binomial probability histograms are approximately normal
  • LO6. Use a simple statistical model (“box model”) to explain the random behaviour of sample sums and means
  • LO7. Use box models as the basis for various statistical tests
  • LO8. 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.

No changes have been made since this unit was last offered.


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.