2012/2013  KAN-CM_SU8K  Statistics for Business and Economics (Cancelled, new statistics course on the way)

English Title

Statistics for Business and Economics (Cancelled, new statistics course on the way)

Course information
Language	English
Exam ECTS	7.5 ECTS
Type	Elective
Level	Full Degree Master
Duration	Summer
Course period	Course cancelled, new statistics courses on the way Further information on www.cbs.dk/summer
Time Table	Please see course schedule at e-Campus
Study board	Study Board for MSc in Economics and Business Administration
Course coordinator
Faculty - Brian Eric Smith, McGill University Stig Hartmann - Department of Accounting and Auditing
Main Category of the Course
Statistics and mathematics
Last updated on 12-01-2012

Learning objectives

To understand the nature of statistical relationships between variables, and to explore the concept of causality. To thoroughly explore regression analysis, including simple linear regression, multiple regression and autoregression. To learn techniques for selecting appropriate regression models for prediction and forecasting in business and economics. To introduce fundamental ideas of experimental design, analysis of variance, and factor analysis. To become familiar with the use of a modern, commercial statistical software package such as would be used by professional statisticians. To be able to critically read and understand regression and factorial models in business, economic and financial research papers.

Prerequisite

Introductory Statistics Course: Compulsory

Examination

Statistics for Business and Economics

4-hour written exam: Type of test Written Exam Marking scale 7-step scale Second examiner No second examiner Exam period Summer Term Aids Please, see the detailed regulations below Duration 4 Hours Exam aids:  Formula Sheet; Calculator (any type); Translation Dictionary. Details to be announced.

Course content

This is a higher level statistics course focusing on advanced regression models with applications in business and economics. The main topics include: Simple linear regression; Multiple regression, including multicollinearity, interaction and data transformations; One-Way Analysis of Variance; Two-way Analysis of Variance; Introduction to Autoregressive models and forecasting.     The course’s development of personal competences:   The course will provide an in-depth analysis of regression techniques in business and finance.  Real data and authentic applications will be used throughout the course. The use of computer software is an essential component of the course and both Excel and Minitab will be employed to assist in the analysis of regression models to solve a variety of practical problems. Students will acquire skills in analyzing relationship between variables and the construction of predictive regression models.

Teaching methods

Lectures; in-class discussion of case studies; use of PowerPoint presentations. Interactive computer modeling.

Expected literature

A Second Course in Statistics: Regression Analysis, 7th Edition (International Edition) William Mendenhall and Terry Sincich Publisher: Pearson