Creation and implementation of research and scientific projects WF-OB-PRBN

Subject outcomes:

W_01 The student verifies statistical hypotheses. The student correctly explains the results of the analyses and applies statistical inference. Course topics: (8, 9, 10, 11, 12, 13, 14, 15). Methods of verifying learning outcomes - Presentation in class

W_02 The student carries out a detailed scientific project. The student constructs summaries and scientific descriptions of the project, schedules for scientific projects, and budgets for scientific projects. The student applies the principles of evaluation and accounting for scientific projects, commercialization of research results, and management of their intellectual property. Course topics: (1, 2, 3, 4, 5, 6, 7).
Methods of verifying learning outcomes - Individual project

U_01 The student performs tests examining the distribution from the sample and analyzes outliers. The student correctly selects and applies parametric and non-parametric statistical tests and explains the analysis of relationships between characteristics. Course topics: (10, 11, 12, 13, 14, 15).
Methods of verifying learning outcomes - Presentation in class

U_02 The student prepares research tasks and project objectives. Class topics: (2, 3, 4).
Methods of verifying learning outcomes - Individual project

K_01 The student critically diagnoses statistical errors in scientific research and presents reliable research results. The student presents reliable schedules and cost estimates for research projects. Class topics: (5, 6, 8, 9, 10, 11, 12, 13, 14, 15).
Methods of verifying learning outcomes – Individual project, Presentation in class

K_02 The student plans to prepare a grant application. The student develops their scientific skills in statistical packages. Class topics: (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15).
Methods of verifying learning outcomes - Individual project, Presentation in class

Field-specific outcomes:

W_01 The graduate knows statistical methods and tools for hypothesis testing, analysis of conclusions, and inference (OB2_W04)

W_02 The graduate knows the methodology of preparing a scientific paper in the field of natural sciences
(OB2_W07)

U_01 The graduate is able to select the appropriate methodology to solve a research or practical problem (OB2_U01)

U_02 Graduates are able to apply the principles of scientific or project work, independently and in a team (OB2_U02)

K_01 Graduates are ready to critically evaluate their knowledge, including recognizing the strengths and weaknesses of their skills, attitudes, and actions (OB2_K01)

K_02 Graduates are ready to expand and improve their professional skills (OB2_K07)

Final assessment criteria:

The final grade for the course is based on the project part (50%) and the statistical part (50%).
Students should not miss more than two classes.

Project part: preparation of a research project.
The condition for passing the project part is the preparation of a research project together with a cost estimate for the research in the form of a Word or PDF file. The project must be submitted by the end of the semester.

Statistical part: an exam to check whether the student has acquired the ability to select the appropriate statistical test for data structure analysis and data processing using the STATGRAPHIC CENTURION program. During the classes, there will be partial assessments of the material in the form of practical application of the procedures learned (presentation on computers). This part of the exam is conducted in real time, at a computer workstation using the STATGRAPHIC CENTURION statistical package. The condition for passing the statistical part is to obtain a positive grade in at least one statistical test – performing a statistical analysis using the indicated statistical test.

Assessment criteria:
Very good grade – research project prepared correctly in its entirety, containing all structural elements with a well-prepared cost estimate; error-free and independently performed statistical analysis with its interpretation.
Good plus grade – research project prepared correctly but with minor errors in the cost estimate; independently performed statistical analysis and interpretation.
Good rating – research project prepared correctly but with basic errors in the cost estimate; statistical analysis and interpretation of results performed independently with little help from the supervisor
Satisfactory plus rating – Minor errors in the content of the project, along with basic errors in the cost estimate; statistical analysis performed independently, but interpretation performed with significant assistance from the supervisor
Satisfactory rating – Errors in the project summary (methods/objectives of the work), errors in the preparation of research tasks, errors in the cost estimate; statistical analysis and interpretation of results performed with the help of the supervisor

The lecturer provides assistance in selecting literature
1. Byrkit DR, Statistics today – a comprahensive introduction. Cummings Publ. Comp. 1987.
2. Marek T, Analiza skupień w badaniach empirycznych – Metody SAHN. PWN, 1989.
3. Łomnicki A. Wprowadzenie do statystyki dla przyrodników, PWN, 2016
4. Blalock H., Statystyka dla socjologów, PWN, 1977.
5. Stanisz A. Biostatystyka, Wyd. UJ, 2005
6. Statgraphics, Inrtersoftland.
7. Szostek K., i inni. 2005. Metody opracowania i prezentacji wyników. [w:] Dziecko Żywieckie, K. Kaczanowski (ed.), Wyd. PiT Kraków. pp. 17-19.

Information on level of this course, year of study and semester when the course unit is delivered, types and amount of class hours - can be found in course structure diagrams of apropriate study programmes. This course is related to the following study programmes:

• Environmental Protection - full-time second cycle studies

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

• Description of WF-OB-PRBN in USOSweb