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

Equivalent units
FIN10002 Financial Statistics
Teaching periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date
Pathways Teaching 3
Location
Hawthorn
Start and end dates
20-October-2025
30-January-2026
Last self-enrolment date
02-November-2025
Census date
14-November-2025
Last withdraw without fail date
12-December-2025
Results released date
10-February-2026
Pathways Teaching 1
Location
Hawthorn
Start and end dates
23-February-2026
29-May-2026
Last self-enrolment date
08-March-2026
Census date
24-March-2026
Last withdraw without fail date
14-April-2026
Results released date
09-June-2026
Pathways Teaching 2
Location
Hawthorn
Start and end dates
22-June-2026
25-September-2026
Last self-enrolment date
05-July-2026
Census date
21-July-2026
Last withdraw without fail date
11-August-2026
Results released date
06-October-2026
Pathways Teaching 3
Location
Hawthorn
Start and end dates
19-October-2026
29-January-2027
Last self-enrolment date
01-November-2026
Census date
17-November-2026
Last withdraw without fail date
15-December-2026
Results released date
09-February-2027

Unit learning outcomes

Students who successfully complete this unit will be able to:
 

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

Teaching methods

Hawthorn

Type Hours per week Number of weeks Total (number of hours)
Online Contact (Synchronous Lectures) 1 12 weeks  12
Face to Face Contact (Class 1) 2 12 weeks  30
Face to Face Contact (Laboratory) 2 12 weeks  30
Unspecified Learning Activities (Independent Learning) 6 12 weeks  78
TOTAL     150

Assessment

Type Task Weighting ULO's
AssignmentIndividual 30% 1,2,3,4,5 
Final-Semester TestIndividual 50% 1,2,3,4 
Online QuizzesIndividual 20% 1,2,3,4,5 

Content

  • Descriptive Statistics
  • Probability and Probability Distributions
  • Correlation and Liner Regression
  • Sampling and Estimation
  • Hypotheses Testing: z-, t- and chi-square methods
  • Data Analytics using Excel and Python

Study resources

Reading materials

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