We introduce the most commonly encountered data types and their properties. We describe the process of data sampling, focusing on the distinction between the sampled statistical population and the collected sample, stressing the need for a carefully designed sampling strategy. We introduce the sample statistics that form the core of data analysis, characterising both the position of values (arithmetic mean, median and others) and the spread of values (e.g. variance). The visualisation of individual variables by histograms and box-and-whiskers plots is introduced and later demonstrated with R code. We also briefly discuss the concept and properties of distribution and probability density functions, addressing discrete and continuous variables separately.
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