Figures are a great way to present data visually. However, there are some important rules to follow when choosing and building plots.

Simple rules to follow when creating plots

• Make sure the data is visible – simple plots are typically better than overly complex ones
• Display patterns in the data clearly
• Be honest, accurately portray the magnitude of changes (i.e. don’t over exaggerate your results)
• Draw your plot clearly, excess stylistic components can hurt instead of help your presentation and use reasonably sized fonts

Types of plots

Histograms

Histograms are used to represent the frequency of observations for a single variable. The shape of the histogram provides a lot of information about that particular variable. They are also used for testing assumptions of certain statistical tests.

Point (scatter) plot

This is one of the simplest and most common way to represent numerical data. In its most basic form, each point is a single observation at a given x and y value.

Bar plots

Bar plots can be used to show associations between categorical variables. Bars can either be stacked or side-by-side.

Violin plots

These plots show the frequency in observations within different groups. Sort of like sideways histograms.

Maps

Maps can be used to convey data. For example, this map is made up of colored cells that represent different types of land use.

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Time series

These plots show the changes of a variable over time.

Simple rules to follow when creating tables

• Display patterns in the data clearly
• Be honest, accurately portray the magnitude of changes (i.e. don’t over exaggerate your results)
• Draw your table clearly, excess stylistic components cn hurt instead of help your presentation and use reasonably sized fonts

Tables in RMarkdown uses Markdown syntax. You can check out the Markdown cheat sheet here.