2019/2020 BA-BBLCO1226U Quantitative Business Research
English Title | |
Quantitative Business Research |
Course information |
|
Language | English |
Course ECTS | 7.5 ECTS |
Type | Mandatory |
Level | Bachelor |
Duration | One Semester |
Start time of the course | Spring |
Timetable | Course schedule will be posted at calendar.cbs.dk |
Study board |
Study Board for BSc and MSc in Business, Language and Culture,
BSc
|
Course coordinator | |
|
|
Main academic disciplines | |
|
|
Teaching methods | |
|
|
Last updated on 23-03-2020 |
Relevant links |
Learning objectives | ||||||||||||||||||||||||
|
||||||||||||||||||||||||
Prerequisites for registering for the exam (activities during the teaching period) | ||||||||||||||||||||||||
Number of compulsory
activities which must be approved: 3
Compulsory home
assignments
During the semester there will be 5 mandatory quizzes where 3 of these must be completed and approved. The quizzes must be submitted individually and they will be assessed (automatically) individually but students are allowed to work on them in groups. The mandatory activities are a preparation for the final exam |
||||||||||||||||||||||||
Examination | ||||||||||||||||||||||||
|
||||||||||||||||||||||||
Course content, structure and pedagogical approach | ||||||||||||||||||||||||
This course introduces you to basic quantitative skills in business analysis, including methods for presenting and characterizing quantitative data, making inferences from data based on the theory of probability and statistics, using data to assess relationships and effects, recognizing potential weaknesses or pitfalls in quantitative analysis, and using data for business decision making. The purpose of the course is to make you an educated user of quantitative methods by introducing you to the main theoretical concepts and issues, rather than giving you an extensive training in the underlying statistical theory. Topics include: data representation and summary measures; exploratory data analysis, data collection and basic experimental design; probability theory and distributions, sampling distributions, confidence intervals, significance tests, contingency tables and Bayesian inference, analysis of proportions, single and multivariate regression analysis, analysis of variance. |
||||||||||||||||||||||||
Description of the teaching methods | ||||||||||||||||||||||||
The course will combine lectures, video clips, and working on weekly problem sets in groups with instructor support ("study cafes"). All lectures are videotaped and vodcasted for later reviewing. Solutions to problem sets are also provided as videos. | ||||||||||||||||||||||||
Feedback during the teaching period | ||||||||||||||||||||||||
During the course, students work in groups on weekly problem sets assignments where the solutions are presented afterwards in video format, including common mistakes we observe. There is also a take-at-home test exam near the end of the lecture period that resembles the real written exam. Feedback is then provided through peer grading of the test exam, where the rubric for the peer grading illustrates how the learning objectives of the course manifest themselves in the grade. | ||||||||||||||||||||||||
Student workload | ||||||||||||||||||||||||
|
||||||||||||||||||||||||
Expected literature | ||||||||||||||||||||||||
|