Financial Statistics

FIN10002 12.5 Credit Points Hawthorn Available to incoming Study Abroad and Exchange students

Duration

  • One Semester or equivalent

Contact hours

  • 36 contact hours

2020 teaching periods

Hawthorn

Higher Ed. Semester 1 Higher Ed. Semester 1

Dates:
2 Mar 20 - 31 May 20

Results:
14 Jul 20

Last self enrolment:
15 Mar 20

Census:
15 Apr 20

Last withdraw without fail:
17 Apr 20

Dates:
2 Mar 20 - 31 May 20

Results:
14 Jul 20

Last self enrolment:
15 Mar 20

Census:
15 Apr 20

Last withdraw without fail:
17 Apr 20

More teaching periods
Higher Ed. Semester 2

Dates:
3 Aug 20 - 1 Nov 20

Results:
8 Dec 20

Last self enrolment:
16 Aug 20

Census:
31 Aug 20

Last withdraw without fail:
18 Sep 20

Swinburne Online

Teaching Period 1 Teaching Period 2

Dates:
9 Mar 20 - 7 Jun 20

Results:
30 Jun 20

Last self enrolment:
22 Mar 20

Census:
3 Apr 20

Last withdraw without fail:
24 Apr 20

Dates:
6 Jul 20 - 4 Oct 20

Results:
27 Oct 20

Last self enrolment:
19 Jul 20

Census:
31 Jul 20

Last withdraw without fail:
21 Aug 20


Prerequisites

Anti-requisite
Students that have successfully completed the unit below should not study FIN10002 as it is similar in content.
 
Alternative Tertiary Entry Program: Students who have passed FIN00001 are exempted from taking this unit and must select another unit in its place with advice from a Course Advice Specialist.
 

Aims and objectives

Financial Statistics provides an introduction to financial mathematics and basic statistics within a financial context. It will assist students to gain an appreciation of what statistical methods can achieve, as well as skills in analysing and interpreting business data and statistical analysis. This unit will focus on data science as an analytical and decision making tool, in a variety of business contexts, with a major emphasis on interpretation and application.

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 the relationship between variables to draw inferences about relationships.