Using descriptive charts to better understand your data
Data visualization is often the starting point of explorative analyses, and R is considered as one of the best tools for this task. But what are the options, if you are not a data scientist (yet), and have limited R knowledge? There are some point&click and drag&drop interfaces for R and ggplot2 to ease the issue. However, ‘having a look on the data’ is perhaps the best inducer and drive to start R programming. Moreover, the script of the first baby-steps can be even reused for later analyses.
This talk will highlight some plotting techniques beyond bar- and pie charts, which can be useful for ‘having a look on the data’, as well as detecting trends or outliers. Data of possible racial bias in football will be used, an example of crowdsourced data science.
Assistant professor, Szent Istvan University
Mark Szalai, PhD, is an ecological modeller investigating plant protection problems, and course leader of introductory and advanced R, dataviz and biostatistics MSc/PhD courses.