ST520: Applied Statistics (5 ECTS)

STADS: 25000001

Level
Bachelor course

Teaching period
The course is offered in the spring semester.

Teacher responsible
Email: hcpetersen@stat.sdu.dk

Timetable
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Comment:
Ubegrænset deltagerantal. Fælles undervisning med ST815 Anvendt statistik.

Prerequisites:
None

Academic preconditions:
The mathematics material from the course FF506 Mathematics, statistics and physics for biology and pharmacy is assumed to be known.

Cannot be taken by students that have passed ST503.

Course introduction
The participants should know the basic principles of and methods for statistical description, analysis and inference in relation to biological research. The participants will learn how to use a statistical software for analyzing data. Furthermore, weight will be put on critical reading of scientific papers, treatises, reports, etc, with regard to applications as well as further mediate the results from these.

Qualifications
The participants will obtain insight into elementary statistical methods, and achieve competences in simple statistical analyses. Furthermore, the will obtain competences in critical evaluation and mediation of research results from the biological sciences. They should be capable of applying the acquired knowledge in relevant situation for:

* utilizing graphics and summary methods for descriptive data analysis;
* describing data using key statistics such as mean, variance, and correlation;
* constructing confidence intervals for key statistics;
* testing simple statistical hypotheses;
* analyzing data using simple regression models;
* designing data collection;
* understanding central elements in published results from statistical analyses of biological data;
* critically evaluating the appropriateness of employed methods and inferences based on these;
* presenting statistical results in non-technical terms;

Expected learning outcome
At course end the student is expected to be able to:

• utilize graphics and summary methods for descriptive data analysis.
• describe data using key statistics such as mean, variance, and correlation.
• construct confidence intervals for key statistics.
• test simple statistical hypotheses.
• analyze data using simple regression models.
• design data collection.
• understand central elements in published results from statistical analyze of biological data.
• critically evaluate the appropriateness of employed methods and inferences based on these.
• present statistical results in non-technical terms.

Subject overview
The foundation for statistical considerations. From population to sample and back again. Basic Parameters and their estimation. Descriptive statistics (tables and graphics). Probabilities and distributions. Hypotheses and principles for tests. Examples of test methods: t-test, chi-square-test. Basic concepts underlying linear models starting from simple linear regression. Basic concepts with regard to study design. Common problems in applied statistics (types of inferential error, mass significance, pseudoreplication).

Literature

Meddeles ved kursets start.

Website
This course uses e-learn (blackboard).

Prerequisites for participating in the exam
None

Assessment and marking:

1. Digital written exam (open book) and written assignments during the course, evaluated collectively, 7-point grading scale, internal examiner. (25000002)

During the course a number of written assignments must be handed in. The evaluation accounts for 20% of the final grade for the course.
The written exam accounts for 80% of the final grade for the course.

Reexamination in the same exam period or immediately thereafter. The re-exam may differ from the ordinary exam.

Expected working hours
The teaching method is based on three phase model.
Intro phase: 28 hours
Skills training phase: 20 hours, hereof:
 - Tutorials: 12 hours
 - Laboratory exercises: 8 hours

Educational activities Study phase: 4 hours

Language
This course is taught in Danish or English, depending on the lecturer. However, if international students participate, the teaching language will always be English.

Course enrollment
See deadline of enrolment.

Tuition fees for single courses
See fees for single courses.