Study programmes / C-HE Horticultural Engineering / Advanced Statistical Methods
Course code:PBM
Course title in language of instruction:Pokročilé biometrické metody
Course title in Czech:Pokročilé biometrické metody
Course title in English:Advanced Statistical Methods
Mode of completion and number of credits:Exam (3 credits)
(1 ECTS credit = 28 hours of workload)
Mode of delivery/Timetabled classes:full-time, 0/2
(full-time, hours of lectures per week / hours of seminars per week)
Language of instruction:Czech
Level of course:master; master continuing
Semester:WS 2019/2020 - FH
Name of lecturer:Ing. Miroslav Vachůn, Ph.D. (examiner, instructor, lecturer, supervisor, tutor)
Prerequisites:Bachelor State Exam
 
Aims of the course:The course builds on basic knowledge gained in the course "Biometrics" or "statistics" at the bachelor's degree. The course Advanced biometric methods, students will be familiar with the basics of advanced multivariate methods. In this course students learn the practical applications of a wide range of multivariate techniques (multivariate regression, cluster analysis, etc.) in biological science disciplines.
Course contents:
1.Advanced biometric methods - basic terms (allowance 0/2)
2.Multivariate data and multivariate distribution (allowance 0/2)
3.Quality control and reliability - Statistical tolerance, control and acceptance (allowance 0/6)
4.Cluster analysis (allowance 0/4)
5.Multiple regression analysis (allowance 0/4)
6.Stepwise regression (allowance 0/2)
7.Principal components Analysis (allowance 0/4)
8.Factor analysis (allowance 0/4)

Learning outcomes and competences:
Generic competences:
 
-ability to analyse and synthesize
-ability to apply knowledge
-ability to communicate with professionals in different field of study
-ability to create new ideas (creativity)
-ability to organize and plan ahead
-ability to solve problems
-ability to speak and write in mother tongue
-ability to work in international context
-ability to work independently
-basic computing skills
-capacity to learn
-designing and managing projects
-general knowledge
-professional knowledge
-science and research skills
-skilled at utilizing and processing information

Specific competences:
 
-Ability to analyse and synthesize
-Ability to apply of branch knowledge for solutions of practice horticulture problems
-Evaluation skills of branch data.
-Skills associated with the use and processing of information
-Students can apply theoretical knowledge into practice statistics
-The ability to properly use the statistical software

Type of course unit:required
Year of study:Not applicable - the subject could be chosen at anytime during the course of the programme.
Work placement:There is no compulsory work placement in the course unit.
Recommended study modules:none
Assessment methods:Using continuous testing students' knowledge, evaluation of individual projects, the course concludes oral examination with practical test (results and interpretation).
 
Learning activities and study load (hours of study load)
Type of teaching methodDaily attendance
Direct teaching
     practice28 h
Self-study
     preparation for exam28 h
     elaboration of reports28 h
Total84 h

Basic reading list
  • MELOUN, M. -- MILITKÝ, J. Statistická analýza experimentálních dat. 2nd ed. Praha: Academia, 2004. 953 p. ISBN 80-200-1254-0.
  • HEBÁK, P. et al. Vícerozměrné statistické metody [1]. 2nd ed. Praha: Informatorium, 2007. 253 p. ISBN 978-80-7333-056-91.
  • HEBÁK, P. -- HUSTOPECKÝ, J. -- MALÁ, I. Vícerozměrné statistické metody [2]. 1st ed. Praha: Informatorium, 2005. 239 p. ISBN 80-7333-036-92.
  • HEBÁK, P. Vícerozměrné statistické metody [3]. Praha: Informatorium, spol. s r.o., 2005. 255 p. ISBN 80-7333-039-3.