Benefits of Graphs
Pictorial models are very useful for analyzing and comparing data and for presenting information about the data to others. Summarizing a data set with a chart or graph often allows us to recognize special characteristics (such as the shape or distribution) of our data that may not be obvious from the numerical statistics. In addition, "pictures" are more easily understood than numerical summaries, even by someone with no formal training.
Graphical analysis has several advantages over numerical techniques for determining fits to data. By presenting data visually, one can make determinations as to the importance of points based on their uncertainties as well as their locations on the graph. Although there are numerical techniques for making these determinations, one finds that a visual analysis provides one of the best (and simplest) approaches.
Many calculators now provide simple regression tools (such as "least squares fit") for determining linear fits to data. These regression tools in general do not account for the certainty of a data point nor do they do point rejection of "bad points". The numerical tools work well if just a simple data fit is required with no detailed analysis or if the consistency of the data is well known and fits are need to many sets of data. In general though, for the first look at some data set, a graph is drawn and used in the analysis.