2018/2019 KAN-CIBSO1061U Applied Business Research
English Title | |
Applied Business Research |
Course information |
|
Language | English |
Course ECTS | 7.5 ECTS |
Type | Mandatory |
Level | Full Degree Master |
Duration | One Semester |
Start time of the course | Autumn |
Timetable | Course schedule will be posted at calendar.cbs.dk |
Study board |
Study Board for MSc in Economics and Business
Administration
|
Course coordinator | |
|
|
Main academic disciplines | |
|
|
Teaching methods | |
|
|
Last updated on 17-12-2018 |
Relevant links |
Learning objectives | ||||||||||||||||||||||||
Learning objectives: At the end of the course you
should be able to:
• Calculate and interpret summary and comparative measures of the data. • Distinguish among different types of quantitative data (categorical, continuous, etc.) and recognize the types of information they provide and their limitations. • Recognize the main types of distributions, how they relate to the nature of data at hand, and how to use them in statistical analysis. • Draw inferences about population characteristics from samples. • Recognize the key features of statistical testing (significance, power, confidence intervals) and conduct statistical tests on data. • Understand the concepts of correlation, partial correlation, single- and multivariate regression, and conduct tests related to such regressions, including residual analysis. • Generate and interpret the output from pre-developed software packages. • Discuss and recommend solutions to problems encountered in the analysis of a specific phenomenon. • Perform hypotheses testing of both simple and more composite hypotheses. • Report and interpret the results of the analysis clearly and effectively to a reader who does not have a technical background in statistics and econometrics. • Use simple time series models and smoothing to construct forecasts and confidence intervals of future variables. • Make recommendations based upon the results of the analysis. |
||||||||||||||||||||||||
Examination | ||||||||||||||||||||||||
|
||||||||||||||||||||||||
Course content and structure | ||||||||||||||||||||||||
This course will introduce students to key methods of
quantitative analysis that are widely applied in business and
economic research. Topics covered include, among others,
representing quantitative data, characterizing the data using
numerical and graphic representations, performing tests and drawing
inference from them, recognizing potential weaknesses and/or
pitfalls of quantitative analysis, and using data for business
decision making such as forecasting. The purpose of the course is
to make students educated users of quantitative analysis by
introducing the main theoretical concepts and issues rather than
giving you an extensive training in the underlying mathematical and
statistical theory. The course emphasizes how to apply various
statistical techniques in the support of decisions in the various
functional areas of business and economics.
|
||||||||||||||||||||||||
Description of the teaching methods | ||||||||||||||||||||||||
Teaching methods: The course consists of 12 lectures,6 tutorials and an introductory session to STATA. A detailed plan of topics to be covered in each lecture, as well as respective readings for each topic, will be presented in the course syllabus to be made available before the start of the course. Lectures focus on presenting theory and insights, although numerical examples will be presented to help better understanding of theoretical concepts. On the other hand, tutorials focus exclusively on applying the concepts to concrete examples using real-world data. The tutorials also provide the hands-on experience to problem-solving. | ||||||||||||||||||||||||
Feedback during the teaching period | ||||||||||||||||||||||||
In the tutorial sessions feedback is provided by the instructor at the end of each session. At the end of the course, a special 2-hour session is arranged for the course coordinator to provide the whole class feedback related to the written exam. | ||||||||||||||||||||||||
Student workload | ||||||||||||||||||||||||
|
||||||||||||||||||||||||
Expected literature | ||||||||||||||||||||||||
Instructor PP slides and supplementary notes, if necessary. Individual academic papers and book chapters downloadable from CBS Library.
|