1. komponenta

Lecture type	Total
Lectures	10
Seminar	15
Practicum	15

* Load is given in academic hour (1 academic hour = 45 minutes)

Scientific disciplines such as nutrition and food safety and analysis provide a range of information that have to be analyzed to reach some conclusions. Interpretation and analysis of results from research in nutrition and food technology requires an understanding of the relationship between the main features of the research studies and the data analysis methods.
Due to large amounts of collected data using surveys and / or lab measurements, there is a need to create a database. The database is a collection of interrelated data stored in external memory to a computer, and the data are also available to various users and programs. Computer language used for querying is the SQL language that will be used. It is based on the relational account provided that the mathematical notation is replaced with keywords, like in the English spoken language.
With help of statistics will be given explanations of the theoretical basis with practical examples of use of regression analysis, impact of "atypical" data to the regression model, construction and comparing of the taxonomy of regression models, as well as hypothesis testing. A basic introduction to the multidimensional regression, planning, cluster analysis (CA) and principal component analysis (PCA) will also be given.
Statistical methods must be suitable from the viewpoint of computer application, so with the practical realization of algorithms deals the theory of programming. One of the main tasks of programming is the preparation and programming according to the selected algorithm. Part of the course that deals with the theory of programming will give an overview of topics such as: the formation and development of algorithms and programs (flowchart), the basic data types and operations (logical operations, forming programming loop), multidimensional data types (fields), and programming using ready-made software packages.
As an integral part of the course is the learning of computer-skills, necessary for the practical part of the course, as well as developing communication skills through discussions about applied data analysis.