In this case we have explored the use of heat maps as an effective means to visualize geographic data. The impressions drawn from the heat maps of cessation expense and cessation expense adjusted for population size are quite different. The choice of which visualization is most appropriate depends on the problem statement and the important messages to be conveyed to your audience. In the smoking cessation class, where only a few graphs and statistics would be desired, the heat maps showing total health care expense and total cessation expense communicates the nationwide magnitude of the health care costs associated with smoking and the efforts being made to prevent smoking. The average total health care cost per capita of $459 per person is another powerful statistic in illustrating smoking related costs.

Correlation analysis quantifies the relationship between continuous variables both in terms of direction and strength of association. Examining correlations can also help identify when adjusted values should be reported. For example, the strong relationship between total health care expense and population size suggests that when comparing these expenses between states, a value adjusted for population size should be reported. Always bear in mind that a correlation established from data does not imply that one variable causes another. Causality must be determined from other evidence found in the problem domain. Interpreting correlations between adjusted and unadjusted variables can be difficult. Finally, only a few of the possible analyses have been presented in this case. There are many more relationships that can be explored from this relatively small data set. Considerable time is required to fully explore the relationships between the relatively small number of variables and to examine the various ways in which the data can be summarized and visualized. It is important to choose only those data visualizations and statistics that will resonate with the audience and communicate the intended message in the time allotted.