Interpreting data: boxplots and tables
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# 4 Conclusion

In this course, you have learned about boxplots and about ways of dealing with data given in tabular form.

A boxplot is a way of presenting certain summary statistics and other characteristics of a data set in graphical form. It gives a quick graphical impression of the location, dispersion and the general pattern of skewness in data set, as well as drawing attention to unusually large or small values. In comparing two or more data sets, it is often useful to draw comparative boxplots (that is, draw boxplots for the data sets on the same diagram against the same scale). These can be used to compare the data sets in terms of location, dispersion and symmetry or skewness. For some data sets that exhibit considerable skewness, this process of comparison is sometimes made easier by transforming the data first.

You have seen how the presentation of data in tabular form can often be improve by following certain guidelines. The labelling of the rows and columns in a table should be clear; unnecessary information should not be included; it may be useful to simplify the numbers in the table (for example, by reducing the number of significant figures presented); and summary statistics or calculation results can often usefully be added to table.

When you are faced with the task of interpreting data in a table, it is very often useful to calculate appropriate rates or proportions to clarify the message of the table. Patterns in the data may also become clearer if an appropriate graph is drawn. Guidelines on the choice of graph have been given. You have seen that it is important to understand how the different numbers in a table relate to one another.

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