Overview

This unit provides students with an introduction to statistics within a financial context. Students will gain an appreciation of what statistical methods can achieve, as well as skills in preparing, analysing and interpreting business data and statistical analysis. Students will also learn how to apply analytical tools to visualise and analyse data. The focus of the unit is on data science as an analytical and decision-making tool, in a variety of business contexts, with a major emphasis on interpretation and application.

Requisites

Teaching periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date
Semester 1
Location
Hawthorn
Start and end dates
03-March-2025
01-June-2025
Last self-enrolment date
16-March-2025
Census date
31-March-2025
Last withdraw without fail date
24-April-2025
Results released date
08-July-2025
Teaching Period 1
Location
Online
Start and end dates
10-March-2025
08-June-2025
Last self-enrolment date
23-March-2025
Census date
04-April-2025
Last withdraw without fail date
02-May-2025
Results released date
Semester 2
Location
Hawthorn
Start and end dates
04-August-2025
02-November-2025
Last self-enrolment date
17-August-2025
Census date
31-August-2025
Last withdraw without fail date
19-September-2025
Results released date
09-December-2025
Teaching Period 3
Location
Online
Start and end dates
03-November-2025
08-February-2026
Last self-enrolment date
16-November-2025
Census date
28-November-2025
Last withdraw without fail date
02-January-2026
Results released date

Learning outcomes

Students who successfully complete this unit will be able to:

  • Identify and apply commonly used techniques for data collection and analysis
  • Apply fundamental concepts of probability and probability distributions to problems in business decision-making
  • Apply statistical inference methods to conduct and explain the results of hypothesis testing
  • Apply simple regression analysis to explain the relationship between variables to draw inferences about relationships
  • Apply technological tools to analyse data for decision-making purposes

Teaching methods

Hawthorn

Type Hours per week Number of weeks Total (number of hours)
On-campus
Class		2.00 12 weeks 24
Online
Lecture		1.00 12 weeks 12
Unspecified Activities
Independent Learning		9.50 12 weeks 114
TOTAL150

Swinburne Online

Type Hours per week Number of weeks Total (number of hours)
Online
Directed Online Learning and Independent Learning		12.50 12 weeks 150
TOTAL150

Assessment

Type Task Weighting ULO's
AssignmentIndividual 40 - 60% 1,2,3,4,5 
ExaminationIndividual 40 - 60% 1,2,3,4 

Content

  • Descriptive Statistics
  • Probability and Probability Distributions
  • Sampling and Estimation
  • Hypotheses Testing
  • Correlation and Linear Regression
  • Data Analytics using Power BI and Python

Study resources

Reading materials

A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.