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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 and economic data analysis using statistical techniques based on the Microsoft Excel spreadsheet. This paper is designed to prepare students to develop skills such as critical thinking, information literacy, research and self-motivation for analysing the information by using regression and time series models. This paper focuses on solving a variety of practical problems using computer spreadsheets.

Paper title Financial Data Analysis
Paper code FINC203
Subject Finance
EFTS 0.15
Points 18 points
Teaching period Semester 1 (On campus)
Domestic Tuition Fees (NZD) $912.00
International Tuition Fees Tuition Fees for international students are elsewhere on this website.

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BSNS 102 or BSNS 112
Pre or Corequisite
FINC 102
ECON 210, STAT 210, STAT 241
Schedule C
Teaching staff

Dr Tahir Suleman

Teaching Arrangements

This paper is taught via lectures and computer labs.


Gary Koop, John Wiley & Sons (2006). Analysis of Financial Data. ISBN: 9780470013212.

Course outline
View the course outline for FINC 203
Graduate Attributes Emphasised
Critical thinking, Information literacy, Research and Self-motivation.
View more information about Otago's graduate attributes
Learning Outcomes

Students who successfully complete the paper will be able to:

  1. Understand of the properties of variables from financial markets
  2. Understand the pragmatic use of statistics in Commerce
  3. Understand and apply the concept of simple and multiple linear regression in the analysis of cross-sectional datasets collected under various contexts
  4. Understand and apply the concept of basic time series regression models
  5. Develop fundamental research skills (such as data collection, data processing, and model estimation and interpretation) in applied financial analysis
  6. Emphasize techniques used by Financial and Economic Analysts

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Semester 1

Teaching method
This paper is taught On Campus
Learning management system

Computer Lab

Stream Days Times Weeks
Attend one stream from
A1 Monday 10:00-10:50 10-14, 16-21
A2 Monday 11:00-11:50 10-14, 16-21
A3 Monday 12:00-12:50 10-14, 16-21
A4 Monday 15:00-15:50 10-14, 16-21
A5 Monday 16:00-16:50 10-14, 16-21


Stream Days Times Weeks
M1 Monday 13:00-14:50 9-14, 16-21
Wednesday 16:00-16:50 9-14, 16-21
Thursday 14:00-14:50 9-14, 16-21