BSTA5100: Semester 2, 2022

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Units BSTA5100 Semester 2 2022 [Online]

Unit of study_

BSTA5100: Mathematical Foundations for Biostatistics

Semester 2, 2022 [Online] - Camperdown/Darlington, Sydney

Overview

This unit aims to develop and apply calculus and other mathematically-based techniques to the study of probability and statistical distributions. This unit covers the foundational mathematical methods and probability distribution concepts necessary for an in depth understanding of biostatistical methods. The unit commences with an introduction to mathematical expressions, followed by the fundamental calculus techniques of differentiation and integration, and essential elements of matrix algebra. The concepts and rules of probability are then introduced, followed by the application of the calculus methods covered earlier in the unit to calculate fundamental quantities of probability distributions, such as mean and variance. Random variables, their meaning and use in biostatistical applications is presented, together with the role of numerical simulation as a tool to demonstrate the properties of random variables.

Unit details and rules

Unit code	BSTA5100
Academic unit	Public Health
Credit points	6
Prohibitions ?	BSTA5001 or BSTA5023
Prerequisites ?	None
Corequisites ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Erin Cvejic, erin.cvejic@sydney.edu.au

Type	Description	Weight	Due	Length
Assignment	Assignment 1 Written assignment	15%	- Due date: 21 Aug 2022 at 23:59	1000 words
Outcomes assessed:
Assignment	Assignment 2 Written assignment	35%	- Due date: 11 Sep 2022 at 23:59	2000 words
Outcomes assessed:
Assignment	Assignment 3 Written assignment	15%	- Due date: 09 Oct 2022 at 23:59	1000 words
Outcomes assessed:
Assignment	Assignment 4 Written assignment	35%	- Due date: 06 Nov 2022 at 23:59	2000 words
Outcomes assessed:
Tutorial quiz	Online quizzes Online MCQ and short-answers	0%	Multiple weeks	Online during modules
Outcomes assessed:

Assessment summary

Assignment 1 covers content from Module 1 and Module 2 (Concepts 1 & 2)
Assignment 2 covers content from Module 2 (Concepts 3 & 4) and Module 3
Assignment 3 covers content from Module 4 and Module 5
Assignment 4 covers content from Modules 1-7

There are also non-assessed online quizzes available for various modules.

Additional information for all assessments will be provided on Canvas.

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	Description
High distinction	85 - 100	When you meet the learning outcomes of the unit at an exceptional standard.
Distinction	75 - 84	When you meet the learning outcomes of the unit at a very high standard.
Credit	65 - 74	When you meet the learning outcomes of the unit at a good standard.
Pass	50 - 64	When you meet the learning outcomes of the unit at an acceptable standard.
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see sydney.edu.au/students/guide-to-grades

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.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

The standard BCA policy for late penalties for submitted work is a 5% deduction from the earned mark for each day the assessment is late, up to 50%.

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.

Learning support

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.

Weekly schedule

WK	Topic	Learning activity
Multiple weeks	Module 1: Numbers and functions	Independent study (10 hr)
	Module 2: Calculus	Independent study (40 hr)
	Module 3: Matrices and determinants	Independent study (10 hr)
	Module 4: Probability concepts	Independent study (10 hr)
	Module 5: Discrete random variables	Independent study (20 hr)
	Module 6: Continuous random variables	Independent study (20 hr)
	Module 7: Multiple random variables	Independent study (10 hr)

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 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

Class notes will be provided for the the mathematical concepts components of the unit.
For the probability and distributions components, the prescribed textbook is: Wackerley DD, Mendenhall W, Schaeffer RL. Mathematical Statistics with Applications. 7th edition. 2008 Thomson Learning, Inc. (Duxbury, Thomson Brooks/Cole) ISBN-13: 978-0-495-11081-1

Learning outcomes

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.

Outcomes
Graduate qualities

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

LO1. Manipulate general mathematical expressions and inequalities
LO2. Understand and apply the essential elements of calculus, including differentiation and integration
LO3. Manipulate and evaluate matrix expressions and calculate inverses of matrices
LO4. Demonstrate an understanding of the meaning and laws of probability
LO5. Recognise common probability distributions and their properties
LO6. Apply calculus-based tools to derive key features of a probability distribution and properties of random variables, such as mean and variance
LO7. Demonstrate skills in simulation of random variables to illustrate and explain statistical concepts

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
Learning outcomes

Responding to student feedback

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

This unit was first delivered in Semester 1 2022, and offered as part of the restructured and revised Biostatistics curriculum. Components of this unit are drawn from previous units entitled Mathematical Background for Biostatistics, and Probability and Distribution Theory. Minor errors in the notes have been corrected, and additional signposting of the connection between calculus and probability sections has been added.

Additional information

This unit is externally delivered through the Biostatistics Collaboration of Australia (BCA).

Students will need access to either Stata or R (or both), however no prior experience is required.

Biostatistics Collaboration of Australia (BCA)

Disclaimer

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.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Disclaimer

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