How should you summarise a dataset? This is what descriptive statistics and statistical graphics are for. A statistic is just a number computed from a data sample. Descriptive statistics provide a means for summarising the properties of a sample of data (many numbers or values) so that the most important results can be communicated effectively (using few numbers). Numerical and graphical methods, including descriptive statistics, are used in exploratory data analysis (EDA) to simplify the uninteresting and reveal the exceptional or unexpected in data.

Plotting data

One of the basic principles of good data analysis is: always plot the data. The brain–eye system is incredibly good at recognising patterns, identifying outliers and seeing the structure in data. Visualisation is an important part of data analysis, and when confronted with a new dataset the first step in the analysis should be to plot the data. There is a wide array of different types of statistical plot useful in data analysis, and it is important to use a plot type appropriate to the data type. Graphics are usually produced for screen or paper and so are inherently two dimensional, even if the data are not.

The variables can often be classified as explanatory or response.