Statistics with (business) economics applications

Academic year: 2006-2007 Course code module FTEBAKM100 Semester: 1st and 2nd semester Credits: 6 Study load (hours) 168 Theory (hours): 30,00 Practice/Exercises(hours): 45,00 Other (hours): Part-time program: Instructor(s) Peter Goos Language of instruction: Dutch Semester exam information: Contract restriction information: 1. Prerequisites *Algemene competenties Mathematics with (Business-)Economic Applications, AE BA1 *Sequentiality 2. Objectives (expected learning outcomes) The general objective of this course is therefore to familiarise our students with the statistical methods used to support policy decisions in the private and public sectors. The Statistics with (Business-)Economic Applications course contributes to the following competences: acquiring a basic understanding of relevant scientific methods and techniques, developing problem-solving skills and powers of analysis, synthesising and integrating different perceptions, learning to apply and assess methods in a critical way. More specifically, students will be able to justify, explain and apply statistical techniques and methods with regard to concrete research questions; they will acquire an understanding of statistical techniques and methods, and will be able to construct accurate reasoning (from analysing the problem to the solutions and conclusion). 3. Course content The course starts with a general introduction to, for instance, what statistics are about, the paradigms of statistics, the collection and measuring of data, measurement scales, types of random samples and random sample errors, etc. In descriptive statistics, we summarise the data by discussing the most important graphic and numerical representations and the choice of the most correct representation. After a brief overview of the probability theory we study random variables, using the most important discrete and continuous distributions as examples. As an introduction to inferential statistics, the concept of ¿sampling and distribution¿ is explained, with the following examples: random sample proportions, random sample averages and the central limit theorem, and finally random sample variance. These concepts then lead to the setting up of reliability intervals and hypothesis testing. After a general introduction on testing, we deal with the most important tests for location, dispersion and distribution for different measurement scales and for 1, 2 or more than 2 populations respectively. The course is entirely based on (business-)economic applications. 4. Teaching method Direct contact: Lectures Exercise sessions Personal work: Assignments - individual 5. Assessment method Exam: Written, without oral presentation Closed book Multiple choice Open questions Written assignment: Without oral presentation 6. Compulsory reading – study material Lecturer's syllabus available at ACCO. Additional examples, slides, exercises and self-tests are provided via Blackboard. 7. Recommended reading - study material There is no additional literature that the students should read. 8. Tutoring Students facing problems with the theoretical concepts and/or exercises are encouraged to contact any of the collaborators of the course. Contact details can be found on Blackboard. laatste aanpassing: last update: 13/11/2006 12:59 ilke.franquet