ST815: Applied statistics (5 ECTS)

STADS: 25002901

Level
Master's level course

Teaching period
The course is offered in the spring semester.

Teacher responsible
Email: hcpetersen@stat.sdu.dk

Timetable
There is no timetable available for the chosen semester.

Comment:
Ubegrænset deltagerantal. Fælles undervisning med ST520 Anvendt statistik.

Prerequisites:
None

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

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 (R) 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, they 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). Reading of papers with statistical analyses in the biological sciences. The student choses and studies individually an advanced topic in applied statistics, such as factorial ANOVA, multiple linear regression or ANCOVA (analysis of covariance), as background for the exam project.

Literature

Meddeles ved kursets start.

Website
This course uses e-learn (blackboard).

Prerequisites for participating in the exam
None

Assessment and marking:
Oral exam based on a written project with individual subject. Pass/fail evaluation, internal censorship; evaluation based on an overall assessment (5 ECTS). (25002902)

Reexamination in the same exam period or immediately thereafter. Reexam can havea another form than 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

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.