Graphical displays are very important in the analysis of data. There are four main functions of graphical displays in data analysis (Snee & Pfeifer 1983).
Exploration, which involves checking data for unusual values, making sure the data meet the assumptions of the chosen analysis and occasionally deciding what analysis (or model) to use.
Analysis, which includes checking assumptions but primarily ensuring that the chosen model is a realistic fit to the data.
Presentation and communication of results, particularly summarizing numerical information (Chapter 19).
Graphical aids, which are graphical displays for specific statistical purposes, e.g. power curves for determining sample sizes.
We describe graphical displays for the first two functions here, and the third in our final chapter, although some graphs are useful for more than one function, e.g. scatterplots of Y against X are important exploratory tools and often the best way of communicating such data to readers.
Exploratory data analysis
Before any formal statistical analysis is carried out, it is essential to do preliminary checks of your data for the following reasons:
to reassure yourself that you do actually have some meaningful data,
to detect any errors in data entry,
to detect patterns in the data that may not be revealed by the statistical analysis that you will use,
to ensure the assumptions of the analysis are met,
to interpret departures from the assumptions, and
to detect unusual values, termed outliers (Section 4.5).
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