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Unit of study_

BUSS1020: Quantitative Business Analysis

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.

Details

Academic unit Business Analytics
Unit code BUSS1020
Unit name Quantitative Business Analysis
Session, year
? 
Semester 1, 2023
Attendance mode Normal day
Location Remote
Credit points 6

Enrolment rules

Prohibitions
? 
ECMT1010 or MATH1005 or MATH1905 or MATH1015 or STAT1021 or ENVX1001 or ENVX1002 or DATA1001 or MATH1115
Prerequisites
? 
None
Corequisites
? 
None
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

Yes

Teaching staff and contact details

Coordinator Erick Li, erick.li@sydney.edu.au
Guest lecturer(s) Bernard Conlon , bernard.conlon@sydney.edu.au
Lecturer(s) Erick Li , erick.li@sydney.edu.au
Steven Sommer, steven.sommer@sydney.edu.au
Tony Shang, ce.shang@sydney.edu.au
Type Description Weight Due Length
Supervised exam
? 
Final Exam
Multiple Choice questions
40% Formal exam period 2 hours
Outcomes assessed: LO1 LO2 LO3
Assignment group assignment Assignment
Conduct a statistical analysis and communicate results.
30% Multiple weeks 2000 words.
Outcomes assessed: LO1 LO3 LO2
Assignment Hwk-A
Calculations and short-answers
1% Week 02
Due date: 27 Feb 2023 at 23:59

Closing date: 04 Mar 2023
Approximately 20 questions.
Outcomes assessed: LO1 LO3
Assignment Hwk-B
Calculations and short-answers.
1% Week 03
Due date: 06 Mar 2023 at 23:59

Closing date: 11 Mar 2023
Approximately 20 questions
Outcomes assessed: LO1 LO3
Assignment Hwk-C
Calculations and short-answers.
1% Week 04
Due date: 13 Mar 2023 at 23:59

Closing date: 18 Mar 2023
Approximately 20 questions
Outcomes assessed: LO1 LO3
Assignment Hwk-D
Calculations and short-answers.
1% Week 05
Due date: 20 Mar 2023 at 23:59

Closing date: 25 Mar 2023
Approximately 20 questions
Outcomes assessed: LO1 LO3
Assignment Hwk-E
Calculations and short-answers.
1% Week 07
Due date: 03 Apr 2023 at 23:59

Closing date: 08 Apr 2023
Approximately 20 questions
Outcomes assessed: LO1 LO3
Supervised test
? 
In-semester test
Multiple choice questions
20% Week 08
Due date: 22 Apr 2023 at 16:00
1 hour
Outcomes assessed: LO2 LO3 LO1
Assignment Hwk-F
Calculations and short-answers.
1% Week 08
Due date: 17 Apr 2023 at 23:59

Closing date: 22 Apr 2023
Approximately 20 questions
Outcomes assessed: LO1 LO3 LO2
Assignment Hwk-G
Calculations and short-answers.
1% Week 10
Due date: 01 May 2023 at 23:59

Closing date: 06 May 2023
Approximately 20 questions
Outcomes assessed: LO1 LO3 LO2
Assignment Hwk-H
Calculations and short-answers.
1% Week 11
Due date: 08 May 2023 at 23:59

Closing date: 13 May 2023
Approximately 20 questions
Outcomes assessed: LO1 LO3 LO2
Assignment Hwk-I
Calculations and short-answers.
1% Week 12
Due date: 15 May 2023 at 23:59

Closing date: 20 May 2023
Approximately 20 questions
Outcomes assessed: LO1 LO3 LO2
Assignment Hwk-J
Calculations and short-answers.
1% Week 13
Due date: 22 May 2023 at 23:59

Closing date: 27 May 2023
Approximately 20 questions
Outcomes assessed: LO1 LO3 LO2
group assignment = group assignment ?
  • Final exam: The exam will cover all material in the unit. The exam will have multiple choice questions involving theory and analysis of data.
  • In-semester test: The test will cover material from the unit up until the week of the test. The test will have multiple choice questions involving theory and analysis of data.
  • Assignment – Students will conduct a statistical analysis of data and be required to communicate their findings in a professional manner via a short video presentation (individual) and a written report of 2000 words (group).
  • Homework – The weekly homework contains mostly numerical questions based on the previous weeks material.
  • 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

Description

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. 

Distinction

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.

Credit

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.

Pass

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. 

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:

For any homework task submitted more than FIVE (5) calendar days after the due date a mark of zero will be awarded. In all other respects, the standard late penalties will apply in accordance with the Assessment Procedures 2011 shown below.

Special consideration

If you experience short-term circumstances beyond your control, such as illness, injury or misadventure or if you have essential commitments which impact your preparation or performance in an assessment, you may be eligible for special consideration or special arrangements.

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.

WK Topic Learning activity Learning outcomes
Week 01 Introduction to Data Lecture and tutorial (4 hr) LO1 LO3
Week 02 Numerical descriptive measures Lecture and tutorial (4 hr) LO1 LO3
Week 03 Basic probability Lecture and tutorial (4 hr) LO1 LO3
Week 04 Discrete probability distributions Lecture and tutorial (4 hr) LO1 LO3
Week 05 Continuous probability distributions Lecture and tutorial (4 hr) LO1 LO3
Week 06 Sampling distributions Lecture and tutorial (4 hr) LO1 LO3
Week 07 Confidence intervals Lecture and tutorial (4 hr) LO1 LO3
Week 08 One-sample tests Lecture and tutorial (4 hr) LO1 LO2 LO3
Week 09 Two-sample tests Lecture and tutorial (4 hr) LO1 LO2 LO3
Week 10 Linear regression 1 Lecture and tutorial (4 hr) LO1 LO2 LO3
Week 11 Linear regression 2 Lecture and tutorial (4 hr) LO1 LO2 LO3
Week 12 Multiple regression Lecture and tutorial (4 hr) LO1 LO2 LO3

Attendance and class requirements

There are two parts to the unit:

  1. Self-paced study modules on Canvas
  2. Weekly 2-hour tutorials/workshops (see your schedule)

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 free to students online from the publisher 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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9
Based on the feedback, we change the exams to supervised tests and maintain the individual component of the project.

You will need access to Microsoft Excel to complete all assessment tasks. The software is available as a free download from University IT.

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.