# 2014/2015  BA-BINBO1333U  Statistics

 English Title Statistics

# Course information

Language English
Course ECTS 7.5 ECTS
Type Mandatory
Level Bachelor
Duration One Quarter
Course period First Quarter, Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
Study Board for BSc in International Business
Course coordinator
• Søren Feodor Nielsen - Department of Finance (FI)
• Statistics and mathematics
Last updated on 03-07-2014
Learning objectives
The goal is to enable the students to interpret, understand and apply basic statistical concepts as they apply in scientific research as well as in everyday life.

The students will become familiar with basic probability theory as a model for randomness, concepts of statistical inference as well as a number of concrete estimators, confidence intervals and test. Statistical software will be introduced.

At the completion of this course the students will be able to:
• 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 in our lives, as well as grasp the crucial concept of a sampling distribution and how it relates to inference methods.
• Choose and justify appropriate descriptive and inferential methods for examining and analyzing data and drawing conclusions.
• Analysis of the association between categorical, discrete, and continuous variables, using contingency tables, correlation, regressions, and analysis of variance.
• Communicate the conclusions of statistical analysis clearly and effectively, i.e identify connections between basic statistics and the real world.
Course prerequisites
None
Examination
 Statistics: Exam ECTS 7,5 Examination form Written sit-in exam Individual or group exam Individual Assignment type Written assignment Duration 4 hours Grading scale 7-step scale Examiner(s) One internal examiner Exam period October and Autumn Term, the regular exam takes place in October. The make-up and re-examination takes place in January. Aids allowed to bring to the exam Limited aids, see the list below and the exam plan/guidelines for further information: Additional allowed aidsBooks and compendia brought by the examineeNotes brought by the examineeAllowed calculatorsAllowed dictionaries Make-up exam/re-exam Same examination form as the ordinary exam If the number of registered candidates for the make-up examination/re-take examination warrants that it may most appropriately be held as an oral examination, the programme office will inform the students that the make-up examination/re-take examination will be held as an oral examination instead. The Make-up and Re-examination takes place according to the same rules as the regular exam. Description of the exam procedure This is an open book exam meaning that all material is allowed (textbook, personal notes, lecture slides, exercise solutions, articles, calculator, etc.). An exception is any electronic device that makes it possible to communicate with others, e.g. USB key. PC exam with access to JMP, LEARN and personal S-drive on CBS network. Students do NOT have access to Internet.
Course content and structure

The major goal of the statistics course is to produce statistically educated students which mean that students should develop statistical literacy and the ability to think and reason statistically.

Statistics is a valuable tool in the practical application of every other science. Emphasis is on interpretation and understanding of simple statistical methods as applied in business, economics, different types of companies or institutions and industries.

The topics of the curriculum are:

a)The basic laws of probability and the most important probability distributions.

b) Descriptive statistics, both numerical and graphical.

c) Statistical inference; estimators, confidence intervals and significance tests of hypotheses.

d) One and two sample tests for means and proportions; paired and unpaired data.

e) Analysis of association using contingency tables and correlation.

f) Regression analysis; simple, multiple, logistic.

g) One-way and two-way analysis of variance, analysis of covariance.

Teaching methods
Lectures, exercise classes and computer workshops