# 2017/2018  BA-BMECV1052U  Statistics

 English Title Statistics

# Course information

Language English
Course ECTS 7.5 ECTS
Type Elective
Level Bachelor
Duration One Quarter
Start time of the course First Quarter
Timetable Course schedule will be posted at calendar.cbs.dk
Max. participants 120
Study board
Study Board for HA/cand.merc. i erhvervsøkonomi og matematik, BSc
Course coordinator
• Mette Asmild - Department of Finance (FI)
• Statistics and quantitative methods
Last updated on 30-06-2017

Learning objectives
To achieve the grade 12, students should meet the following learning objectives with no or only minor mistakes or errors: The basic objective of this course is to familiarize the students with the principles of probability theory and statistics. The student will acquire knowledge about what statistics and probability are and expand their experience base by applying a variety of probability and statistical principles in exercises and case studies. The goal is to enable the students to interprete and understand basic statistical concepts as they apply in business, economics, different types of companies or institutions and industries.

Following the course the students can:
• Identify key theories, models and concepts of probability and statistics.
• Use graphical and numerical methods for exploring and summarizing data on a single categorical or quantitative variable.
• Describe basic probability and how probability helps us understand randomness.
• Choose and justify appropriate descriptive and inferential methods for examining and analyzing data and drawing conclusions.
• Analyze the association between categorical, discrete, and continuous variables, using contingency tables, correlation, regressions, and analysis of variance.
• Communicate the conclusions and interpretations of statistical analysis.
Course prerequisites
None
Examination
Course content and structure

The course will, through lectures and exercises, cover:

• Descriptive statistics, both numerical and graphical.
• Statistical inference; estimator, confidence intervals and significance tests of hypotheses.
• Analysis of contingency tables.
• Regression analysis; simple, multiple and covariance analysis.
• One-way and two-way analysis of variance.
Teaching methods
Lectures, exercises and computer classes.
Feedback during the teaching period
Discussions with lecturer and teacing assistant during lectures, exercises and computer workshops. Final exam only asessed with a grade, with no personal feedback. Answer to exam paper will be made available after the exam, enabling the students to compare their answers to the correct ones in order to understand the grade awarded.