Accessibility Skip to Global Navigation Skip to Local Navigation Skip to Content Skip to Search Skip to Site Map Menu

FINC203 Financial Data Analysis

A second course in business statistics with an emphasis on data analysis in finance problems.

The main aim of the paper is to provide students with a course in financial data analysis based on the Microsoft Excel spreadsheet.

Paper title Financial Data Analysis
Paper code FINC203
Subject Finance
EFTS 0.1500
Points 18 points
Teaching period First Semester
Domestic Tuition Fees (NZD) $813.45
International Tuition Fees Tuition Fees for international students are elsewhere on this website.

^ Top of page

Prerequisite
BSNS 102 or BSNS 112 (passed with a grade of at least C+)
Pre or Corequisite
FINC 102 or FINQ 102
Restriction
ECON 210, STAT 241
Schedule C
Commerce
Notes
MATH170 will be accepted as an alternative to FINC 102 or FINQ 102 when that paper has already been passed or where a student is enrolled for both a BCom and another degree for which MATH 170 is required.
Contact
accountancyfinance@otago.ac.nz
Teaching staff
Dr Lynn McAlevey
Teaching Arrangements
Lectures (optional help sessions and computer labs)
Textbooks
Dielman, T.E. Applied Regression Analysis, 4th edition (Duxbury Press)
Course outline
View the course outline for FINC 203
Graduate Attributes Emphasised
Communication, Critical thinking, Information literacy, Self-motivation.
View more information about Otago's graduate attributes.
Learning Outcomes
Students will gain an understanding of the properties of variables from financial markets and the pragmatic use of statistics in commerce, emphasising techniques used by financial analysts. While the paper is recommended for students proceeding in Finance, the methodology is perfectly general and will be useful for any business discipline.

^ Top of page

Timetable

First Semester

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
Blackboard

Lecture

Stream Days Times Weeks
Attend
M1 Monday 14:00-15:50 9-15, 17-22
Wednesday 14:00-15:50 9-15, 17-22

A second course in business statistics with an emphasis on data analysis in finance problems.

The main aim of the paper is to provide students with a course in financial data analysis based on the Microsoft Excel spreadsheet.

Paper title Financial Data Analysis
Paper code FINC203
Subject Finance
EFTS 0.1500
Points 18 points
Teaching period First Semester
Domestic Tuition Fees (NZD) $829.65
International Tuition Fees Tuition Fees for international students are elsewhere on this website.

^ Top of page

Prerequisite
BSNS 102 or BSNS 112 (passed with a grade of at least C+)
Pre or Corequisite
FINC 102 or FINQ 102
Restriction
ECON 210, STAT 241
Schedule C
Commerce
Notes
MATH170 will be accepted as an alternative to FINC 102 or FINQ 102 when that paper has already been passed or where a student is enrolled for both a BCom and another degree for which MATH 170 is required.
Contact
accountancyfinance@otago.ac.nz
Teaching staff
To be advised.
Teaching Arrangements
Lectures (optional help sessions and computer labs)
Textbooks
Dielman, T.E. Applied Regression Analysis, 4th edition (Duxbury Press)
Course outline
View the course outline for FINC 203
Graduate Attributes Emphasised
Communication, Critical thinking, Information literacy, Self-motivation.
View more information about Otago's graduate attributes.
Learning Outcomes
Students will gain an understanding of the properties of variables from financial markets and the pragmatic use of statistics in commerce, emphasising techniques used by financial analysts. While the paper is recommended for students proceeding in Finance, the methodology is perfectly general and will be useful for any business discipline.

^ Top of page

Timetable

First Semester

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
Blackboard

Computer Lab

Stream Days Times Weeks
Attend one stream from
Z1 Monday 09:00-09:50 11, 13, 16, 18, 20, 22
Z2 Monday 10:00-10:50 11, 13, 16, 18, 20, 22
Z3 Monday 12:00-12:50 11, 13, 16, 18, 20, 22
Z4 Monday 13:00-13:50 11, 13, 16, 18, 20, 22
Z5 Monday 11:00-11:50 11, 13, 16, 18, 20, 22

Lecture

Stream Days Times Weeks
Attend
M1 Monday 14:00-15:50 9-13, 15-22
Wednesday 14:00-15:50 9-13, 15-16, 18-22