| Learning objectives |
To achieve the grade 12, students
should meet the following learning objectives with no or only minor
mistakes or errors: Identify different types of quantitative data
and explain basic methods of data collection and experimental
design
- Use and critically evaluate the use of graphics, tables, and
summary measures to illustrate relationships in data, appropriate
for the purpose at hand
- Use elementary theory of probability and distributions to
calculate sample distributions and the probabilities of alternative
outcomes and make basic statistical inferences (tests) about
population characteristics from samples
- Use and interpret the output of methods to statistically
analyze associations, such as contingency tables and single and
multiple regression and recognize common problems and limitations
in such methods
- When faced with a specific research question and available
data, select one or more appropriate statistical methods to address
the question, develop a structured and disciplined approach to
statistical analysis critically evaluate the
results
|
| Examination |
|
Kvantitativ
Metode:
|
| 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 |
Summer and Summer |
| Aids allowed to bring to the exam |
Limited aids, see the list below:
- Written sit-in-exam with pen and paper
- Written sit-in-exam on CBS' computers
- Books and compendia brought by the examinee
- Allowed dictionaries
- Allowed calculators
- Notes in paper format brought by the examinee
- Access to personal drive (S-drive) on CBS' network
- USB key to upload your notes before the exam
- Access to all information on CBSLearn
|
| 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.
|
Description of the exam
procedure
You may turn in computer-printed or hand-written pages in any
combination.
|
|
| Course content and
structure |
|
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, and single and
multivariate regression analysis.
|
| Teaching methods |
| In the course, we will combine a
number of different learning formats. We will make extensive use of
video recordings of short lectures on particular theoretical
subjects that you can view at home in conjunction with your reading
and problem solving. Plenary lectures will be highly interactive;
theory lectures will focus on interactions to help you understand
the theoretical concepts and principles; application lectures will
focus on how to apply the theories and methods to concrete
problems. There will be a weekly problem set which you are strongly
encouraged to complete, preferably in study groups. Weekly tutorial
sessions give you an opportunity to work on the problem sets with
teacher assistance. Teaching will emphasize real-world data
examples and conceptual understanding rather than detailed
knowledge of procedures and theories. |
| Student workload |
| Attending lectures |
40 hours |
| Attending tutorials |
20 hours |
| Written exam and feedback |
6 hours |
| Homework and reading |
159 hours |
|
| Expected literature |
- Michael Barrow, Statistics for Economics, Accounting and
Business Studies, 6e, Pearson Education, 2014, with online course
material access. ISBN: 9780273788508
-
Video lectures, uploaded on Learn
-
On-line datasets and problem sets
-
Supplementary notes/articles
-
Microsoft Excel software (for descriptive data
analysis).
-
JMP statistical software (CBS student
license)
|
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