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Visual displays should effectively and succinctly communicate key information.
Visual displays in Statistics are often referred to as graphs or charts. We saw in Visual Displays – One Variable how the choice of graph to represent a single variable is determined by the variable type. So too when we wish to display pairs of variables, the variable types of the pair of variables determine which visual display is appropriate.
The visual display’s title, and each of the vertical and horizontal axes must be clearly labelled, informative and unambiguous.
Graphs summarise data to communicate key information clearly and succinctly. Patterns in the graphs displaying data from two variables provide information about the relationship or association between the two variables.
The appropriate graphs to display each combination of variable types are:
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Both numerical → scatterplot
- Both categorical → clustered bar chart
- 1 numerical and 1 categorical → histograms vertically aligned (or side by side boxplots)
Before You Watch
Now What?
Now that you have learnt about visual displays for two variables you should consider the methods of testing for associations (relationships) between two variables in the Hypothesis test videos (Comparing two groups: t tests and Chi-squared test) and the Correlation and Regression videos .
But When Am I Going to Use This?
Across all fields of study we measure characteristics, or random variables. We often are interested in more than one measure, and also whether the two measures (variables) are related. For example, is a chemical reaction time associated with the amount of a catalyst used, or is response time, or even cognitive load associated with age, or sex? Visually displaying data arising from pairs of variables well enables the identification of patterns and effective communication of key information. This may be used in organisational reports, presentations to key stakeholders, reporting upon research and investigations or any other similar forum or endeavour. Say less, show more!
Other Links
Learn about the importance of labels at GCSE Science website
Take graphs to the limit with Gapminder, Hans Rosling and his 'Joy of Stats'