Teaching materials for R workshop tuaght at the University of Agder (Norway).
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How much information we get out of data often depends on our ability to produce, change, and reshape data frames. Getting data into the right shape for analysis often requires substantially more time than the statistical analysis itself but is rarely part of the usual statistics curriculum for social science. Fortunately, data wrangling has never been easier thanks to the R package tidyverse. In this workshop I will teach the fundamental tidyverse functions to provide access to a remarkable set of tools to process data for analysis in only a few lines of code.
In data science it is well known that important aspects of the data might be missed if the analyst relies on descriptive and inferential data summaries only. Being able to fluently change between data visualisation tools gives us access to information that summary statistics might conceal; appropriate visualisation tools can help us to communicate otherwise complicated findings and convince our readers. In this workshop I will introduce the grammar of graphics as a conceptual framework for data visualisation and, using examples and exercises, I will explain how this framework is implemented in the widely used and incredibly flexible R package ggplot2.