| Learning objectives |
To achieve the grade 12, students should meet the
following learning objectives with no or only minor mistakes or
errors: Upon completion of the course, the students should be able
to:
- Explain different kinds of population characteristics (types of
variables), their measurement from a sample, and sampling
biases.
- Explain and discuss the concept of probability and the concept
of inference, and relate to measures of test statistics, critical
value, confidence interval and p-value. Understand the concept of
inference.
- Explain and perform appropriate tests of hypotheses about means
and proportions
- Explain and perform tests of hypotheses about the association
between two categorical variables.
- Explain the concept of correlation between numerical variables,
and compute a correlation coefficient
- Explain the logic of regression analysis and the difference
between correlation and regression analyses. Formulate and discuss
adequate regression models for explaining different phenomena.
- Perform linear regression, including multivariate regression
and regression with categorical (dummy) variables as explanatory
variables. Interpret regression coefficients and related measures
(t-tests, F-tests, standard errors, p-values etc.) and the
determination coefficient (R2), and investigate
residuals.
|
| Course prerequisites |
| English language skills equal to B2 level (CEFR)
and math skills equal to Danish level B are recommended |
| Examination |
|
Method II.
Statistics and quantitative methods:
|
| 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 |
Spring |
| 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 addresses established statistical methods for
representing and analyzing quantitative data, primarily survey
data. The focus will be on selecting and applying the
methods that are appropriate for a given type of
data. Students will learn how phenomena can be measured and
analyzed statistically, how to report the results of their
analysis, and what kind of conclusions statistical research
can lead to.
The main modules composing the course are:
• Probability
• Confidence intervals and hypothesis testing
• Tests of hypotheses about means and proportions
• Tests of association between categorical variables
• Correlation analysis
• Regression analysis
Students will learn how to perform statistical analyses in
Microsoft Excel.
|
| Teaching methods |
| Lectures (introduce statistical theory, example,
cases); workshops (train how to select, apply and report the
appropriate method for analyzing a particular data set); homework
exercises (in preparation for lectures and workshops). |
| Feedback during the teaching period |
Feedback during term:
• Office hours
• Follow-up on workshop assignment during following week’s lectures
Feedback after exam:
• Suggested answers for exam questions
• Office hours (one week) for individual queries
|
| Student workload |
| Classes |
30 hours |
| Reading and homework exercises |
130 hours |
| Attending workshops |
10 hours |
| Preparation for written exam |
55 hours |
|
| Expected literature |
- Alan Agresti and Christine Franklin: ‘Statistics. The Art
and Science of learning from Data’, 3rd Edition.
Pearson Education International. Chapters 1, 3, 4, and 6-13.
Exclusive of sections 4.3, 6.3, 7.3, 8.5, 9.6, 11.5, 13.6).
529 pages
- Per Vejrup-Hansen: 'Excel for Statistics. How to
Organize Data'. Samfundslitteratur 2013. 80
pages
Please note, minor changes may occur. The
teacher will upload the final reading list to LEARN two weeks
before the course starts.
|
Permalink