| Learning objectives |
The goal is to enable the students to interpret,
understand and apply basic statistical concepts as they apply in
scientific research as well as in everyday life.
The students will become familiar with basic probability theory as
a model for randomness, concepts of statistical inference as well
as a number of concrete estimators, confidence intervals and test.
Statistical software will be introduced.
At the completion of this course the students will be able to:
- 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 in our lives, as well as grasp the crucial
concept of a sampling distribution and how it relates to inference
methods.
- Choose and justify appropriate descriptive and inferential
methods for examining and analyzing data and drawing
conclusions.
- Analysis of the association between categorical, discrete, and
continuous variables, using contingency tables, correlation,
regressions, and analysis of variance.
- Communicate the conclusions of statistical analysis clearly and
effectively, i.e identify connections between basic statistics and
the real world.
|
| Course prerequisites |
| None |
| Examination |
|
Statistics:
|
| 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 |
October and Autumn Term, the regular exam takes
place in October. The make-up and re-examination takes place in
January. |
| Aids allowed to bring
to the exam |
Limited aids, see the list below and the exam
plan/guidelines for further information:
- Additional allowed aids
- Books and compendia brought by the examinee
- Notes brought by the examinee
- Allowed calculators
- Allowed dictionaries
|
| 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.
The Make-up and Re-examination takes
place according to the same rules as the regular
exam.
|
Description of the exam
procedure
This is an open book exam meaning that
all material is allowed (textbook, personal notes, lecture slides,
exercise solutions, articles, calculator, etc.). An exception is
any electronic device that makes it possible to communicate with
others, e.g. USB key.
PC exam with access to JMP, LEARN and personal S-drive on CBS
network.
Students do NOT have access to
Internet.
|
|
| Course content and structure |
|
The major goal of the statistics course is to produce
statistically educated students which mean that students should
develop statistical literacy and the ability to think and reason
statistically.
Statistics is a valuable tool in the practical application of
every other science. Emphasis is on interpretation and
understanding of simple statistical methods as applied in business,
economics, different types of companies or institutions and
industries.
The topics of the curriculum are:
a)The basic laws of probability and the most important probability
distributions.
b) Descriptive statistics, both numerical and graphical.
c) Statistical inference; estimators, confidence intervals and
significance tests of hypotheses.
d) One and two sample tests for means and proportions; paired and
unpaired data.
e) Analysis of association using contingency tables and
correlation.
f) Regression analysis; simple, multiple, logistic.
g) One-way and two-way analysis of variance, analysis of
covariance.
|
| Teaching methods |
| Lectures, exercise classes and computer
workshops |
| Student workload |
| Lectures |
28 hours |
| Exercise classes |
18 hours |
| Computer workshops |
6 hours |
|
| Expected literature |
|
Book: Agresti A., C. Franklin (2012): “Statistics: The Art and
Science of Learning from Data” (3rd international ed), Prentice
Hall; chapters 1-14.
Supplementary notes
Please note, minor changes might occur. The teacher will
upload the final reading list to Learn two weeks before the course
starts.
|
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