Search
Here we show the best projects completed during the first year of the assignment. We originally planned to select one to three, but in the end we decided to showcase four. Our goal is to give next year’s students examples of the kind of work we’d like to see—but, more importantly, to brag a little.
We selected the following final projects (in alphabetical order, with the language of the submitted report):
You can view the student's submissions for yourself here.
Students in this work show how rich sources of data are the official statistics, namely the Statistical Office of the SR. The work starts with a retrospective look at the effects of the legislative novelization of 2009, then the characteristics of different regions, and concludes with an investigation of the security on railway crossings. We recognize this work for creativity in obtaining data and hard-core statistical approach to their investigations.
This very grounded work stems from research done in the TAČR project “Apparatus for non-invasive automatic analysis of hemodynamic parameters” at the Department of Physics. The work targeted a clinical problem of how to estimate a hardly measurable parameter needed for the Pulse Wave Velocity (PWV) measurement of arterial stiffness. Students analyzed their dataset in-depth and investigated the options for predicting the jugulum-aortic bifurcation from other known information about the patient, like BMI or arm circumference. The outcome of this work was a simple model that could, on the tested population, replace a cumbersome measurement in the clinical practice of preventing cardiovascular diseases. We recognize this work for its contribution to ongoing research and clear direction of applying the methods from the course to get a solution for a practical problem.
The project focused on analyzing the socioeconomic factors that affect newborn mortality in different countries using global UNESCO and WorldBank data. The work identified what the data show to be the most prominent factors in high mortality rates, looked into commonalities between countries, and identified cases of exception. Students showed a wide range of techniques covering almost all of the course topics and even investigated beyond when needed. Although the topic was not original, the solution was sound, and students put their results into the context of other similar studies, providing a detailed comparison.
A very original work that analyzed an important contemporary question using data from the Czech Statistical Office (ČSÚ). The project set out to study the effect of the influx of Ukrainian refugees on the job market in the Czech Republic and, in particular, the unemployment rate of women. We especially recognized the originality of the work and that students studied well beyond the scope of the course to apply techniques from timeseries analysis.
Here we present the best projects completed during the second year of the assignment. This year, students had the advantage of seeing last year’s exemplary projects, and the overall quality of work matched those standards. In general, the teams handled task definition and project management very well, although they did not always reach sufficient analytical depth. We hope to see further improvements in this regard in the third year.
You can view the full student's submissions for yourself here.
This study examined the neurophysiological effects of classic and novel psychoactive substances in rats using EEG. Distinct drug classes produced characteristic spectral signatures—psychedelics and cannabinoids suppressed power, while dissociatives, stimulants, and opioids enhanced specific frequency bands. Machine learning reliably classified pharmacological groups, and links between EEG changes and behavioral states such as locomotion were identified. These findings support EEG as a tool for mapping drug effects and identifying biomarkers of toxicity and therapeutic potential.
This project analyzed regional healthcare quality in the Czech Republic using mortality and hospitalization rates as outcomes. Multivariate models revealed that hospitalization was strongly influenced by healthcare resources, including staff numbers and bed availability, whereas mortality showed weak associations with socioeconomic factors. Regions were grouped based on model predictions, highlighting disparities such as high hospitalization in Prague and lower rates in surrounding areas. The findings underscore the importance of equitable allocation of healthcare personnel and infrastructure to improve regional healthcare accessibility and efficiency.
This study investigated whether the proportion of foreigners in Czech districts affects crime rates. Linear and generalized linear models were used, incorporating socioeconomic confounders such as unemployment, debt enforcement, and social benefits. The share of foreigners remained a statistically significant predictor of overall crime, particularly for property offenses and general endangerment. Further analyses revealed that the effect was primarily driven by male foreigners and certain nationalities. While other unobserved factors cannot be ruled out, the results suggest a robust association between the foreign population share and regional crime patterns.