(in Polish) Statistical methods for molecular diagnostic 2600-DM-SM-2-S2

Classes include the application of mathematical and statistical methods in molecular diagnostic, description of relationships by means of basic linear and nonlinear functions, different types of data transformations, basic statistical distributions, parametric and nonparametric significance tests and linear regression, classification and ordination

Term 2021/22L:

Term 2022/23L:

Term 2023/24L:

Term 2024/25L:

Total student workload

Contact hours with teacher: - participation in laboratory - 18 hrs - consultations - 10 hrs Self-study hours: - preparation for laboratory - 10 hrs - reading literature - 10 hrs - preparation for final test - 30 hrs Altogether: 78 hrs (3 ECTS)

Learning outcomes - knowledge

Student W1: has knowledge how to prepare presentations and reports and mathematical knowledge in the field of data processing and analysis K_W20 W2: defines a task or problem in the field of his specialty and selects appropriate statistical methods to solve them K_W21

Learning outcomes - skills

Student U1: is able to apply statistical methods and interpret of obtained results in the field of molecular diagnostic K_U06 U2: is able to use a foreign language to communicate at a basic level in accordance with the requirements of B2 ESOKJ K_U20

Learning outcomes - social competencies

Student K1: can work in a team, both by directing and co-ordinating the team's activities and by performing assigned tasks K_K09

Teaching methods

Expository teaching methods: discussion, presentation, video / computer, pointer, banners image

Observation/demonstration teaching methods

- staging
- display

Expository teaching methods

- participatory lecture
- problem-based lecture

Exploratory teaching methods

- project work
- practical
- laboratory
- seminar
- case study

Online teaching methods

- cooperation-based methods
- content-presentation-oriented methods
- methods referring to authentic or fictitious situations

Type of course

compulsory course

Prerequisites

Basic knowledge of statistics in the field of first degree studies.

Course coordinators

Term 2023/24L:

Term 2022/23L:

Term 2021/22L:

Term 2024/25L:

Assessment criteria

Laboratory – project in groups 61-68% satisfactory, 69-76% satisfactory plus, 77-84 % good, 85- 92% good plus, 93-100% very good W1, W2, U1, U2, K1

Practical placement

not applicable

Bibliography

Łomnicki A. 2012. Statystyka dla przyrodników. PWN.
Stanisz A. 2006. Statystyka dla biologów na przykładach z medycyny. Statsoft.
Zar J.H. 2010. Biostatistical analysis. Prentice Hall, Pearson International Edition.

Additional information

Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system:

Description of 2600-DM-SM-2-S2 in USOSweb