Course
Statistics For Business and Economics (BØK356)
"The world’s most valuable resource is no longer oil, but data." The Economist (2017). The global economy is increasingly driven by knowledge accumulation, transfer, and utilization. However, how can data be turned into information and eventually into knowledge? This question is not restricted to empirical researchers, analysts and data scientists. It is also crucial for business managers. Data sourcing, information processing and analyzing these are at the core of modern managerial tasks. This requires that managers know how to collect, process, and crucially, analyze small and large data sets. They also need to know how to transform the results of their analyses into easy-to-understand visualizations and informative presentations to share their insights with others. The course BØK356 focuses on analytical skills that will help students to work with given and structured data. In addition to basic statistical concepts, students will also learn to work with the empirical software R.
Course description for study year 2020-2021. Please note that changes may occur.
Semesters
Facts
Course code
BØK356
Credits (ECTS)
10
Semester tution start
Spring
Language of instruction
English
Number of semesters
1
Exam semester
Spring
Content
Typical subject areas covered are:
- Introduction into R
- Descriptive statistics such as distributional characteristics (mean, median, …)
- Bivariate statistics such as group comparisons (t-test etc.)
- Correlation analysis
- Bivariate & multivariate OLS regression (OLS)
Expectations: 280 ECTS work hours divided on lectures, in-class and out-of-class work, exercises and independent study.
Central literature
- Grolemund, G., Wickham, H. 2017. "R for Data Science", O'Reilly Media
- James, Witten, Hastie and Tibshirani. 2013. "An Introduction to Statistical Learning: with Applications in R"
Learning outcome
Knowledge
On completion of the course, students will gain knowledge in:
- Basic programming in R
- Describing and comparing distributions
- Fundamental concepts of bivariate statistics
- Basic binary and multivariate regression analysis
- Regression diagnostics
Skills
Upon completion of this course, students will be able to:
- Import and export data into R
- Use R to construct different measures and variables
- Condense information into meaningful indices and metrices
- Assess and compare empirical variables
- Conduct basis econometric analyses in bivariate and multivariate settings.
Required prerequisite knowledge
Exam
Coursework requirements
The course involves a number of pass/fail projects focusing on the use of R, which are compulsory to all students and are required to be admitted to the final exam.
Students are required to attend at least 80% of the classes. Students failing the exam will be allowed to participate in the course in the subsequent year. Exemptions from this rule will be decided on an individual basis.