Business Analytics

BUSS1020

Quantitative Business Analysis

3.9
35 verified reviews
Credit Points
6
Session
2026 Sem 1
Location
Camperdown/Darlington
Attendance
Normal
Unit Overview
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.

Requirements

Prohibitions
ECMT1010 or MATH1005 or MATH1905 or MATH1015 or MATH1115 or STAT1021 or ENVX1001 or ENVX1002 or DATA1001 or DATA1901

Unit Reviews

A
Anonymous
2017 • Semester 1
4

If you have a decent maths background you'll be fine. There's little point in attending lectures or tutes, the textbook is better than both 90% of the time, just watch the recording right before assessments since Richard will state the answers i.e. how to do the assignment.

A
Anonymous
2017 • Semester 1
5

Good subject

A
Anonymous
2017 • Semester 1
3

Pick the right lecturer!

A
Anonymous
2017 • Semester 2
4

Great teaching team and fairly straightforward content, especially if you come from a statistics background.

A
Anonymous
2016 • Semester 1
5

Very difficult unit if you aren't a maths person or didn't do maths in high school but all things considered this is one of the best compulsory units USYD's business school offers. Plenty of opportunities for 'free marks'- the weekly homework and first quiz. However difficulty level increases very very quickly and quiz 2 and the final exam are notably more challenging. The only compulsory to include a group assignment, however, which is laborious and you run the risk of uncooperative group members. P.S. unit is very easy to self-teach, lecture and tutorial attendance largely unnecessary

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Semester Roadmap

W01
Introduction to DataLecture
Introduction to DataWorkshop
W02
Numerical descriptive measuresLecture
Numerical descriptive measuresWorkshop
W03
Basic probabilityLecture
Basic probabilityWorkshop
W04
Discrete probability distributionsLecture
Discrete probability distributionsWorkshop
W05
Continuous probability distributionsLecture
Continuous probability distributionsWorkshop
W06
Sampling distributionsLecture
Sampling distributionsWorkshop
W07
Confidence intervalsLecture
Confidence intervalsWorkshop
W08
One-sample testsLecture
One-sample testsTutorial
W09
Two-sample testsLecture
Two-sample testsWorkshop
W10
Linear regression 1Lecture
Linear regression 1Workshop
W11
Linear regression 2Lecture
Linear regression 2Workshop
W12
Multiple regressionLecture
Multiple regressionWorkshop

Support

Teaching Staff

Bernard Conlon
bernard.conlon@sydney.edu.au
Coordinator

Assessments

Final Exam
40%
Formal exam period
Written examAI prohibited
Homework A-C (EFT)
5%
Multiple weeks
Out-of-class quizAI allowed
Homework D-K
10%
Multiple weeks
Out-of-class quizAI allowed
In-semester test
20%
19 Apr 2026 at 12:10
Written testAI prohibited
Assignment
25%
Week 13
Data analysisAI allowed