This initial exploration of the appointment backlogs and characteristics of the VA medical centers followed a progression beginning with univariate graphs followed by bivariate and multivariate visualizations. While it is tempting to jump right in and look for relationships between variables, it is important to first visualize each variable individually. Not only does it focus the analyst on the observed magnitude and variation for each variable, it allows outliers to be identified. Outliers may be unusual observations or data errors that warrant further investigation and in the case of data errors correction or removal.

Visualizations are an effective way to familiarize both the analyst and stakeholders with the data available for analysis and the variations between the VA hospitals. Plotting this information on a map adds geographic context. The exploratory analysis allows us to form initial impressions about the relationships between variables and develop hypotheses. However, it does not allow us to definitively answer questions such as “Has there been a significant change in the appointment backlogs from 2015 and 2016?” In the next case, we will make use of statistical tests of hypothesis to address such questions.