Among the most important are distribution and variability factors (145-146; 164; 175), with particular attention to the central limit theorem (166), and margin of error (179-186). If practitioner understand how these factors apply to statistical calculations, and how they impact the validity and potential reliability of the study, then statistical claims can be properly evaluated based on the reported values in the research being considered or produced. Evaluating the accuracy of actual statistical calculations is often beyond the abilities of practitioners. But evaluating the way the numbers yield information which addresses the trends and speaks to the causal tendencies in data is critical for understanding statistical studies. Rumsey presents summarized treatments of basic correlative and associative measures used in statistical data, and points out that anyone can evaluate such calculations to determine what types of errors might exist in any...

The practitioner should be aware of common errors in statistical calculations -- specifically regarding claims made that can't actually be supported, or supportable claims that were missed in the analysis (277-228). Further, the practicing professional should understand how proper research design affects results, such as, for example, building appropriate hypotheses which are tested against null hypothesis to test for acceptance (219-220), and finding an adequate sample size that has been randomly selected for the study so that bias is avoided (313). If the practitioner utilizes these concerns when either building statistical studies or (more likely) evaluating their claims, then the ability to accurately use data derived from statistical studies should be a benefit rather than a hindrance to the professional endeavor.
Works Cited

Rumsey, D. (2003). Statistics for Dummies. Hoboken,…