Program Overview

Overview

The BUSS1020: Quantitative Business Analysis unit is designed to equip graduates with the ability to use quantitative techniques to analyze business problems. This unit is crucial in all business disciplines, as it deals with increasing amounts of data and expectations of quantitative skills. The unit covers interpreting data involving uncertainty and variability, modeling and analyzing relationships within business data, and making correct inferences from the data.

Unit Details and Rules

• Academic unit: Business Analytics
• Credit points: 6
• Prerequisites: None
• Corequisites: None
• Prohibitions: 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: Yes

Teaching Staff

• Coordinator: Nurul Alam

Assessment

The assessment for this unit includes:

• Supervised exam: Final exam, 60% of the total mark, 2 hours, due in February exam weeks
• Small test: Class Quiz, 10% of the total mark, 0.5 hours, due in Week 01
• Assignment: Group Assignment Part 1, 15% of the total mark, 750 words, due in Week 02
• Assignment: Group Assignment Part 2, 15% of the total mark, 1000 words, due in Week 04

Early Feedback Task

This unit includes an early feedback task designed to give students feedback prior to the census date. Details are provided in the Canvas site, and the result will be recorded in the Marks page.

Assessment Summary

• Final exam: Covers all material in the unit from both lectures and practical classes, with a mixture of multiple-choice questions and short answer questions involving theory and analysis of data.
• Assignments: Two parts, Part 1 due in Week 2 and Part 2 due in Week 4, both worth 15% of the total mark.
• Class Quiz: Individual, covering topics one and two, with a mixture of multiple-choice questions and short answer questions.

Assessment Criteria

The University awards common result grades, with the following mark ranges and descriptions:

• High distinction: 85-100, exceptional standard
• Distinction: 75-84, very high standard
• Credit: 65-74, good standard
• Pass: 50-64, acceptable standard
• Fail: 0-49, does not meet the learning outcomes of the unit to a satisfactory standard

Late Submission

Penalties apply when written work is submitted after 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 University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously. Similarity detection software is used to detect potential instances of plagiarism or other forms of academic integrity breaches.

Learning Support

• Simple extensions: Available for up to five calendar days through a simple extension application process
• Special consideration: Available for longer periods or essential commitments that impact performance in an assessment
• Support for students: The University offers various support services, including health and wellbeing services, financial support, and learning support

Weekly Schedule

The unit is taught over four weeks, with the following topics and learning activities:

• Week 01: Introduction to Data, Numerical descriptive measures, Basic probability
• Week 02: Discrete probability distributions, Continuous probability distributions, Sampling distributions
• Week 03: Confidence intervals, One-sample tests, Two-sample tests
• Week 04: Linear regression 1, Linear regression 2, Multiple regression

Learning Outcomes

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

• LO1: Use a variety of analytical and statistical tools to analyze 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. These include:

• GQ1: Depth of disciplinary expertise
• GQ2: Critical thinking and problem-solving
• GQ3: Oral and written communication
• GQ4: Information and digital literacy
• GQ5: Inventiveness
• GQ6: Cultural competence
• GQ7: Interdisciplinary effectiveness
• GQ8: Integrated professional, ethical, and personal identity
• GQ9: Influence

Additional Information

• Required readings: Berenson et al, (2019). Basic business statistics: concepts and applications, US Edition, (14e), Pearson, New York
• Software requirements: Microsoft Excel, 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 enrollment numbers.