| Learning objectives |
To achieve the grade 12, students
should meet the following learning objectives with no or only minor
mistakes or errors: 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 |
Autumn, 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:
- Books and compendia brought by the examinee
- Allowed dictionaries
- Allowed calculators
- Notes in paper format brought by the examinee
- Additional allowed aids, please see the list
below
|
| 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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