Elements of statistical data analysis 1400-217ESAD
The course aims to familiarize students with the methods of statistical data analysis most commonly used in biological and environmental sciences and their application using the R package. Practical exercises are supplemented with necessary theoretical explanations of basic statistical concepts.
The classes are designed to provide students with the practical skills necessary for processing their own research results, as well as to facilitate the understanding of statistical analyses of research results in scientific articles.
The classes cover topics such as statistical description, graphical presentation of data, statistical inference in the field of comparisons of means, fractions, correlations, linear regression; basic experimental designs and analysis of variance.
The first part of the course will focus on learning the basics of using the R package, and the second part will focus on performing statistical analyses with its help.
Type of course
Mode
Prerequisites (description)
Course coordinators
Learning outcomes
KNOWLEDGE
Knows the principles of research planning and modern data collection techniques (K_W06Os2, K_W02Bl2)
Has knowledge of statistical inference, knows and understands the principles of biological science methodology (K_W07Os2)
Recognizes the need to use advanced statistical methods to describe phenomena and analyze data in the studied field of biological sciences (K_W08BI2)
Knows specialized bioinformatics tools necessary for solving problems in the studied field of biological sciences (K_W09BI2)
SKILLS
Applies appropriate statistical methods, algorithms, and IT techniques to describe phenomena and analyze biological data (K_U06BI2),
Applies advanced statistical methods and tools to analyze empirical data and describe natural processes (K_U01Os2)
Is able to collect and interpret empirical data (K_U10Os2)
SOCIAL COMPETENCES
Has the habit of using objective sources of scientific information (K_K09Os2)
Broadens interests in the direction of exact sciences (K_K03Os2)
Critically analyzes information appearing in the mass media and is able to use it in practice (K_K10BI2)
Is able to convey knowledge about the latest achievements in natural sciences to the public and explain the rationale for conducting basic scientific research (K_K03BI2
Assessment criteria
Two short written tests using the R program and a final written test using the R program; 51% of the points from all tests combined are required to pass.
Bibliography
Biecek P. 2008. Przewodnik po pakiecie R. Oficyna Wydawnicza GiS.
Walesiak M., Gatnar E. 2009. Statystyczna analiza danych z wykorzystaniem programu R. Wydawnictwo Naukowe PWN.
Aczel A.D. 2006. Statystyka w zarządzaniu. Wydawnictwo Naukowe PWN
Dobosz M. 2001. Wspomagana komputerowo statystyczna analiza wyników badań. Akademicka Oficyna wydawnicza EXIT.
Koronacki J., Mielniczuk J. 2006. Statystyka dla studentów kierunków technicznych i przyrodniczych. Wydawnictwo Naukowo-Techniczne.
Łomnicki A. 2003. Wprowadzenie do statystyki dla przyrodników. Wydawnictwo Naukowe PWN.
Mądry W. 1998. Doświadczalnictwo. Doświadczenia czynnikowe. Wykłady i ćwiczenia. Fundacja ROZWÓJ SGGW.
Petrie A., Sabin C. 2006. Statystyka medyczna w zarysie. Wydawnictwo Lekarskie PZWL.
Watała C. 2002. Biostatystyka - wykorzystanie metod statystycznych w pracy badawczej w naukach biomedycznych. a-medica Press.
Wołek J. 2006. Wprowadzenie do statystyki dla biologów. Wydawnictwo Naukowe Akademii Pedagogicznej, Kraków.
Shahbaba B. 2012. Biostatistics with R. An Introduction to Statistics Through Biological Data. Seria: Use R!. Springer.
Additional information
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:
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: