Students often believe that statistical significance is the only determinant of whether a quantitative result is "important." In this paper, I review traditional null hypothesis statistical testing to identify what questions inferential statistics can and cannot answer, including statistical significance, effect size and direction,…

Written by a social worker for social work students, this is a nuts and bolts guide to statistics that presents complex calculations and concepts in clear, easy-to-understand language. It includes numerous examples, data sets, and issues that students will encounter in social work practice. The first section introduces basic concepts and terms to…

This paper presents a large-scale, comprehensive test of generalized trust across 31 nations. I pay particular attention to the theory and measurement of voluntary associations in promoting trust, hypothesizing that voluntary associations connected to other voluntary associations are more beneficial for the creation of generalized trust than…

Replication is important to viable scientific inquiry; results that will not replicate or generalize are of very limited value. Statistical significance enables the researcher to reject or not reject the null hypothesis according to the sample results obtained, but statistical significance does not indicate the probability that results will be…