ABSTRACT
Once you have a collection of observations from your environmental study, you should thoroughly examine the data in as many ways as possible and relevant. When the first widely available commercial statistical software packages came out in the 1960s, the emphasis was on statistical summaries of data, such as means, standard deviations, and measures of skew and kurtosis. It is still true that “a picture is worth a thousand words,” and no amount of summary or descriptive statistics can replace a good graph to explain your data. John Tukey coined the acronym EDA, which stands for Exploratory Data Analysis. Helsel and Hirsch (1992, Chapters 1, 2, and 16) and USEPA (1996) give a good overview of statistical and graphical methods for exploring environmental data. Cleveland (1993, 1994) and Chambers et al. (1983) are excellent general references for methods of graphing data. This chapter discusses the use of summary statistics and graphs to describe and look at environmental data.
