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2011/2012  BA-BLC_1QBR  Quantitative business research

English Title
Quantitative business research

Course Information

Language English
Point 7,5 ECTS (225 SAT)
Type Mandatory
Level Bachelor
Duration One Semester
Course Period Spring
Time Table Please see course schedule at e-Campus
Study Board
Study Board for BSc og MSc in Business, Language and Culture
Course Coordinator
  • Christian Erik Kampmann - Department of Innovation and Organizational Economics
Main Category of the Course
  • Statistics and mathematics
Last updated on 29 maj 2012
Learning Objectives
  • • Distinguish different types of quantitative data and present them in graphical and summary forms appropriate for the purpose at hand.
  • • Use elementary probability theory and distributions to calculate probabilities of alternative outcomes.
  • • Estimate and make basic statistical inferences (tests) about population characteristics from samples.
  • • Calculate and use measures of correlation, partial correlation, single- and multivariate regression analysis, and conduct simple tests related to such regressions, using a pre-developed software package.
  • • Use simple time series models and smoothing to construct forecasts and confidence intervals of future variables.
  • • Calculate the net present value and other standard financial measures of profitability of cash flow profiles and use such measures to evaluate alternative investment prospects.
  • • Account at a basic level for the concept of risk and expected utility theory.
  • • Demonstrate how to find, evaluate, and analyze real-world data in the context of a research question.
Quantitative business research
Quantitative business research:
Assessment Home Assignment
Marking Scale 7-step scale
Censorship Internal examiners
Exam Period May/June
Aids Open Book, Written and Electronic Aid is permitted
Duration 72 Hours
Individually home assignment, 5 pages
Course Content

This course introduces students to basic quantitative skills in business analysis, including methods of representing quantitative data, characterizing this data using various summary measures and graphic representations, making inferences from the data based on the theory of probability and statistics, recognizing potential weaknesses or pitfalls in quantitative analysis, and using data for business decision making such as quality control, forecasting, and investment analysis. The purpose of the course is to make students educated users of quantitative methods, allowing them to interpret the output from pre-developed software tools, such as Excel packages, by introducing the main theoretical concepts and issues rather than giving them an extensive training in the underlying statistical theory. The course includes basic numeracy skills (a refresher of high-school level mathematics), graphing techniques, spreadsheets and statistical software, methods of data collection, summary measures of location and spread, index numbers and measures of change, elementary probability theory, main statistical distributions, estimation and inference from population samples, hypothesis testing, correlation, single and multivariate regression analysis and residual analysis, forecasting using time series and smoothing, and financial mathematics and investment analysis. Furthermore, students will have the opportunity to apply these techniques to a real-world problem in the term paper required to pass the course. The term project will be based on a selection from a list of predefined topics that are representative of the typical issues studied in the first-year project in the following term.

Teaching Methods
Lectures and tutorial exercises, culminating in a term project. Lectures focus on presenting theory and insights. Tutorials focus on applying these to concrete exercises. The term project gives students the opportunity to apply the tools and methods to a more realistic problem.

To be announced on Learn, but most likely:

  • [M]: Morris, Clare (2008) Quantitative Approaches in Business Studies (7th ed.), Prentice-Hall
    ISBN 978‑0‑273‑70889‑6.
  • Companion on-line material for the textbook.
  • Supplementary notes uploaded by instructor.