This tutorial, directed primarily toward students doing research projects, is intended to help them do four things: (1) Decide if their data gathering activity can yield numerical data that will permit a meaningful hypothesis test. (2) If it will, decide if one of the tests described would be useful. (3) If so, apply that test, and (4) Adequately explain the use of the test so their readers can have confidence in their analysis. It is not intended to be a text for a complete statistics course - only a guide to few relatively simple tests . Complex hypothesis testing procedures are not covered. For example, the discussion of Analysis of Variance (ANOVA) introduces what is called one way ANOVA. Two way ANOVA, a more complex procedure involving the use of blocking variables, is not covered. It simply presents a few commonly used tests and down-to-earth explanations of how to use them. It is intended to be a low cost supplement that can help its reader understand a few commonly-used tests. It was put together on a shoestring by a non-mathematician for the benefit of other non-mathematicians -- or for mathematicians who have forgotten some or all of the statistics they have studied. There are no color illustrations or professionally-prepared charts and graphs. Economy was a guiding principle. Four brief introductory chapters discuss numbers, basic terms, measures of central tendency and dispersion, probability, and data presentation. With that background the book then introduces various tests and explains them in down to earth language.
About the Author: Dr. G. is a retired university professor. He supervised graduate level research projects for more than twenty years and found that students often encountered frustration and project delay because they lacked understanding of the basics of hypothesis testing. These students needed tutorial help to pick and choose among various types of simple tests they could apply to their research data and then could proceed successfully. Developing a formal course to prepare students for research projects, he determined to include in that course an introduction to hypothesis testing that would give students practical help - brief lectures, practice problems, and problem solutions for discussion. His book is a direct result of that practical experience. It is intended to be an easy to understand tutorial that will help the student researcher develop and test a hypothesis meaningful to his or her research objective.