Contents	Introduction	Descriptive	Hypothesis	Tables	Appendix

The Research Methods Handbook was developed to serve as a quick reference for undergraduate and graduate liberal arts students taking research methods courses. The Handbook augments classroom lecture and commonly available statistical texts by providing an easy to follow outline for conducting and interpreting hypothesis tests. It was not designed as a standalone statistical text, although some may wish to use it concurrently with a comprehensive lecture series.

The Handbook focuses on reinforcing the importance of assumptions and employing a systematic process to determine statistical significance. The common statistical packages in use today make it far too easy for novices to forget the important and sometimes complex underpinnings of hypothesis testing. In addition, review questions and critical interpretation exercises are provided to build skills in the practical application of research methods. The guiding philosophy of the Handbook is the belief that although students should be able to conduct basic research they are more likely to be confronted with statistics produced and reported by others rather than conducting statistical investigations themselves. To encourage this development of both production and interpretative skills, critical review exercises are provided throughout the handbook.

The Handbook also contains review questions that use a statistics calculator called StatCalc (included in AcaStat software). Although the Handbook can be used with or without StatCalc, the statistics calculator augments the Handbook by providing students with the means to evaluate how the results of statistical applications will vary as key data requirements are altered (such as sample size and variance). Generally the only other alternatives for varying data were to either redo calculations by hand or alter data files in the more common statistical software.

A suggested approach for beginning students is to initially have the students conduct hypothesis testing by hand and indicate in the p-value positions whether their test shows p >.05 (not significant) or p = .05 (statistically significant). After discussing the results, have the students use StatCalc to estimate the actual p-values for each comparison. This exercise will help students connect alpha with p-values, traditional classroom instruction with real world application, and reinforce that the hypothesis testing process along with all its steps and assumptions about the data must underpin each and every p-value they interpret.