| Learning objectives |
To achieve the grade 12, students should meet the
following learning objectives with no or only minor mistakes or
errors: The basic objective of this course is to familiarize the
students with the principles of probability theory and statistics.
The student will acquire knowledge about what statistics and
probability are and expand their experience base by applying a
variety of probability and statistical principles in exercises and
case studies. The goal is to enable the students to interprete and
understand basic statistical concepts as they apply in business,
economics, different types of companies or institutions and
industries.
Following the course the students can:
- Identify key theories, models and concepts of probability and
statistics.
- Use graphical and numerical methods for exploring and
summarizing data on a single categorical or quantitative
variable.
- Describe basic probability and how probability helps us
understand randomness.
- Choose and justify appropriate descriptive and inferential
methods for examining and analyzing data and drawing
conclusions.
- Analyze the association between categorical, discrete, and
continuous variables, using contingency tables, correlation,
regressions, and analysis of variance.
- Communicate the conclusions and interpretations of statistical
analysis.
|
| Course prerequisites |
| None |
| Examination |
|
Statistics:
|
| 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 |
Autumn |
| 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
At all written
sit-in exams the student has access to the basic IT application
package (Microsoft Office (minus Excel), digital pen and paper,
7-zip file manager, Adobe Acrobat, Texlive, VLC player, Windows
Media Player). PLEASE NOTE: Students are not allowed to communicate
with others during the exam :
Read more about exam aids and IT application
packages here |
| 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 |
|
The course will, through lectures and exercises, cover:
- Descriptive statistics, both numerical and graphical.
- Statistical inference; estimator, confidence intervals and
significance tests of hypotheses.
- Analysis of contingency tables.
- Regression analysis; simple, multiple and covariance
analysis.
- One-way and two-way analysis of variance.
|
| Teaching methods |
| Lectures, exercises and computer
classes. |
| Feedback during the teaching period |
| Discussions with lecturer and teacing assistant
during lectures, exercises and computer workshops. Final exam only
asessed with a grade, with no personal feedback. Answer to exam
paper will be made available after the exam, enabling the students
to compare their answers to the correct ones in order to understand
the grade awarded. |
| Student workload |
| Attending lectures |
28 hours |
| Attending exercises |
18 hours |
| Attending computer (JMP) workshops |
4 hours |
| Attending exam |
4 hours |
| Preparation for lectures |
30 hours |
| Preparation for exercises |
20 hours |
| Preparation for JMP workshops |
12 hours |
| Revisions before exam |
90 hours |
|
| Expected literature |
|
Book: Agresti A., C. Franklin (2014): “Statistics: The Art and
Science of Learning from Data, Perason New International Edition”,
Third Edition.
Supplementary notes
|
Permalink