| Learning objectives |
- Identify different types of quantitative data and explain basic
methods of quantitative 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 in data, such as contingency tables, single
and multiple regression, and analysis of variance, 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
- Account for some inherent pitfalls and limitations in
statistical analysis as it is done in practice and suggest ways
such problems may be mitigated.
|
| Examination |
|
Quantitative
Business Research:
|
| Exam
ECTS |
7,5 |
| Examination form |
Written sit-in exam on CBS'
computers |
| Individual or group exam |
Individual exam |
| Assignment type |
Written assignment |
| Duration |
4 hours |
| Grading scale |
7-step scale |
| Examiner(s) |
One internal examiner |
| Exam period |
Summer and Summer |
| Aids |
Limited aids, see the list below:
The student is allowed to bring - USB key for uploading of notes, books and compendiums in a
non-executable format (no applications, application fragments, IT
tools etc.)
- Any calculator
- Books (including translation dictionaries), compendiums and
notes in paper format
The student will have access to - Access to CBSLearn
- Access to the personal drive (S-drive) on CBS´ network
- Advanced IT application package
|
| 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.
|
|
| 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, 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 |
| Attending lectures |
40 hours |
| Attenting study cafes |
30 hours |
| Written exam |
4 hours |
| Test exam and peer grading |
12 hours |
| Home preparation |
120 hours |
| Total |
206 hours |
|
| Expected literature |
-
Agresti, et al. (2018) Statistics: The Art and Science of
Learning from Data (4th global ed.). Pearson, ISBN
1-292-16477-8.
-
[S]: Simmons et al. (2011) False-Positive Psychology:
Undisclosed Flexibility in Data Collection and Analysis Allows
Presenting Anything as Significant. Psychological Science 20(10):
1-8.
-
Companion on-line and electronic material for the textbook
(Supplementary)
-
On-line homework assignments and data sets, uploaded on
Learn.
-
Supplementary notes, instructional videos and misc. material,
uploaded on Learn.
-
JMP software
-
Microsoft Excel software
-
Microsoft Word software
|
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