The quantitative relationships shown in this survey were the only ones that met a minimum (p<.05) standard for significance testing. That served as a convenient way to discard results that didn’t prove interesting. For current purposes, though, statistical significance isn’t a particularly relevant measure.
Statistical significance has a very defined meaning. In broadly simplified terms, it means that the result one finds in a sample group is likely also to be true of the entire population one samples from. It requires that the overall population be well defined, and that the sample be randomly chosen from among that full population. Our convenience sample for this survey was neither a random sample, nor was it drawn from a well-defined overall population; therefore statistical significance is an irrelevant measure for our use.
The best way to view the findings here, then, is with cautious interest. The results we show here are interesting, and there’s a reasonably good likelihood they represent reality as applied to some overall population (particularly one whose demographics match the sample’s). The results match theory, which lends them credence. Therefore, it’s probably not a bad idea to test these results by putting their implications into practice in real ministry situations. Anything more definitive than that is hard to say, however.