Overview
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.
About this paper
| Paper title | Financial Data Analysis |
|---|---|
| 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. |
- Prerequisite
- BSNS 102 or BSNS 112
- Pre or Corequisite
- FINC 102
- Restriction
- ECON 210, STAT 210, STAT 241
- Schedule C
- Commerce
- Contact
- accountancyfinance@otago.ac.nz
- Teaching staff
Dr Tahir Suleman tahir.suleman@otago.ac.nz
- Teaching Arrangements
This paper is taught via lectures and computer labs.
- Textbooks
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:
- Understand of the properties of variables from financial markets
- Understand the pragmatic use of statistics in Commerce
- Understand and apply the concept of simple and multiple linear regression in the analysis of cross-sectional datasets collected under various contexts
- Understand and apply the concept of basic time series regression models
- Develop fundamental research skills (such as data collection, data processing, and model estimation and interpretation) in applied financial analysis
- Emphasize techniques used by Financial and Economic Analysts
Timetable
Overview
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.
About this paper
| Paper title | Financial Data Analysis |
|---|---|
| Subject | Finance |
| EFTS | 0.15 |
| Points | 18 points |
| Teaching period | Semester 1 (On campus) |
| Domestic Tuition Fees | Tuition Fees for 2024 have not yet been set |
| International Tuition Fees | Tuition Fees for international students are elsewhere on this website. |
- Prerequisite
- BSNS 102 or BSNS 112
- Pre or Corequisite
- FINC 102
- Restriction
- ECON 210, STAT 210, STAT 241
- Schedule C
- Commerce
- Contact
- accountancyfinance@otago.ac.nz
- Teaching staff
Dr Tahir Suleman tahir.suleman@otago.ac.nz
- Teaching Arrangements
This paper is taught via lectures and computer labs.
- Textbooks
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:
- Understand the properties of variables from financial markets
- Understand the pragmatic use of statistics in Commerce
- Understand and apply the concept of simple and multiple linear regression in the analysis of cross-sectional datasets collected under various contexts
- Understand and apply the concept of basic time series regression models
- Develop fundamental research skills (such as data collection, data processing, and model estimation and interpretation) in applied financial analysis
- Emphasise techniques used by Financial and Economic Analysts