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Unit of study_

BUSS1020: Quantitative Business Analysis

Semester 1, 2020 [Normal day] - Camperdown/Darlington, Sydney

All graduates from the BCom need to be able to use quantitative techniques to analyse business problems. This ability is important in all business disciplines since all disciplines deal with increasing amounts of data, and there are increasing expectations of quantitative skills. This unit shows how to interpret data involving uncertainty and variability; how to model and analyse the relationships within business data; and how to make correct inferences from the data (and recognise incorrect inferences). The unit will include instruction in the use of software tools (primarily spreadsheets) to analyse and present quantitative data.

Unit details and rules

Unit code BUSS1020
Academic unit Business Analytics
Credit points 6
ECMT1010 or MATH1005 or MATH1905 or MATH1015 or STAT1021 or ENVX1001 or ENVX1002 or DATA1001 or MATH1115
Assumed knowledge

Mathematics (equivalent of band 4 in the NSW HSC subject Mathematics or band E3 in Mathematics Extension 1 or 2) OR MATH1111

Available to study abroad and exchange students


Teaching staff

Coordinator Bernard Conlon,
Type Description Weight Due Length
Final exam Final exam
50% Formal exam period 2.5 hours
Outcomes assessed: LO1 LO3 LO2
Small continuous assessment Weekly homework
Short answer and MCQ
20% Multiple weeks Approximately 10-15 questions
Outcomes assessed: LO1 LO3 LO2
Assignment Individual assignment 1
Short answer and MCQ
15% Week 09
Due date: 03 May 2020 at 23:59

Closing date: 03 May 2020
20 questions
Outcomes assessed: LO1 LO3
Assignment Individual assignment 2
26/04/20 23:59
15% Week 13
Due date: 31 May 2020 at 23:59

Closing date: 31 May 2020
20 questions
Outcomes assessed: LO1 LO2 LO3

Assessment summary

  • Weekly homework: Online homework will be assigned almost every week, starting in week 2. The best 4 of the last 6 homeworks will be used to calculate the final grade for this assessment item
  • Individual assignment 1: Online assignment covering unit content from weeks 1-8.
  • Individual assignment 2: Online assignment covering unit content from weeks 9-13.
  • Final exam: The final exam will examine all unit content from weeks 1-13.

Detailed information for each assessment can be found 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


High distinction

85 - 100

Awarded when you demonstrate the learning outcomes for the unit at an exceptional standard, as defined by grade descriptors or exemplars outlined by your faculty or school. 


75 - 84

Awarded when you demonstrate the learning outcomes for the unit at a very high standard, as defined by grade descriptors or exemplars outlined by your faculty or school.


65 - 74

Awarded when you demonstrate the learning outcomes for the unit at a good standard, as defined by grade descriptors or exemplars outlined by your faculty or school.


50 - 64

Awarded when you demonstrate the learning outcomes for the unit at an acceptable standard, as defined by grade descriptors or exemplars outlined by your faculty or school. 


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.

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:

For the homework tasks no late work will be accepted as answers will be released immediately after the due date. For the individual assignments a late penalty of 5% per day will be applied for 10 days after which time the assignment will not be accepted.

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 1. Introduction; 2. Data types; 3. Sampling data Lecture and tutorial (4 hr) LO1 LO3
Week 02 Organising and visualising data Lecture and tutorial (4 hr) LO1 LO3
Week 03 1. Numerical descriptive measures; 2. Introduction to probability Lecture and tutorial (4 hr) LO1 LO3
Week 04 1. Basic probability; 2. Random variables Lecture and tutorial (4 hr) LO1 LO3
Week 05 Discrete probability distributions Lecture and tutorial (4 hr) LO1 LO3
Week 06 Continuous probability distributions Lecture and tutorial (4 hr) LO1 LO3
Week 07 1. Sampling distributions; 2. Confidence interval estimation Lecture and tutorial (4 hr) LO1 LO3
Week 08 1. Confidence interval estimation; 2. Hypothesis testing: one-sample tests Lecture and tutorial (4 hr) LO1 LO2 LO3
Week 09 Hypothesis testing: one-sample tests and two-sample tests Lecture and tutorial (4 hr) LO1 LO2 LO3
Week 10 Hypothesis testing: two-sample tests (ctd) Lecture and tutorial (4 hr) LO1 LO2 LO3
Week 11 Simple linear regression 1 Lecture and tutorial (4 hr) LO1 LO2 LO3
Week 12 1. Simple linear regression 2; Introduction to multiple regression Lecture and tutorial (4 hr) LO1 LO2 LO3
Week 13 1. Multiple regression; 2. Conclusions Lecture and tutorial (4 hr) LO1 LO2 LO3

Attendance and class requirements

Lecture recordings: All lectures and seminars are recorded and will be available on Canvas for student use. Please note the Business School does not own the system and cannot guarantee that the system will operate or that every class will be recorded. Students should ensure they attend and participate in all classes.

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

Berenson et al, (2019). Basic business statistics: concepts and applications, US Edition, (14e), Pearson, New York. (ISBN: 9780134684840)

The unit text will be available to students online from the publisher, Pearson via Canvas.

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. use a variety of analytical and statistical tools that are useful for analysing business data
  • LO2. identify and test a hypothesis from a business perspective using data
  • LO3. communicate quantitative and statistical findings or results in a professional and ethical manner with a focus on business context.

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.

The unit has been redesigned with the help of the Business School's CLaS team. The assessment scheme has been adjusted to reduce the number of assessments and to allow students to analyse a real-world data set in workshops for their group assignment. Introducing new online teaching module to engage students.


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.