Search for: [Abstrakt = "The functional principal components analysis combines the advantages of the standard principal components analysis and enables analysing data of a dynamic nature. The main difference in both methods is the type of data\: the PCA is based on multivariate data, whereas the FPCA on the functional data including curves and trajectories, i.e. a series of individual observations, not a single observation, as usual. The purpose of the article is to apply functional principal components analysis to the problem of student’s achievements. The article was compared the level of knowledge presented by students during various stages of education in 2009\-2017. The analysis covers the average exam results after the second, third and fourth stage of education. The functional principal components analysis, based on functional data, will be used in the analysis. This method allows the analysis of dynamic data"]

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