When Forsyth Futures is making comparisons between communities or across years, it conducts statistical tests to make sure that analysts are at least 95% sure that the observed differences are a result of actual differences between the two measures, not a result of random chance or the sampling method used. Statisticians refer to these kinds of differences as statistically significant differences. This is why readers may notice that Forsyth Futures reports will refer to communities as having a similar measures even when the estimates for those measures appear different at face value. Forsyth Futures only identifies measures as different if there is a statistically significant difference between them at the 95% confidence level.
When users are analyzing datasets themselves, they can use the 95% confidence interval described above as a rough estimate of statistical significance. If the 95% confidence intervals for two measures do not overlap, then any difference between the measures is likely to be statistically significant. However, the differences can be statistically significant even if the confidence intervals overlap.