Expanded and updated, the Third Edition of Gopal Kanji's best-selling resource on statistical tests covers all the most commonly used tests with information on how to calculate and interpret results with simple datasets. The Third Edition now includes: - a new introduction to statistical testing with information to guide even the non-statistician through the book quickly and easily - real-world explanations of how and when to use each test with examples drawn from wide range of disciplines - a useful Classification of Tests table - all the relevant statistical tables for checking critical valu.

As the number of tests has increased, so has the pressing need for a single source of reference. Bringing together the hundred most commonly used tests, this volume provides just such an indispensable aid for student and statistician alike. An introduction discusses the principles of hypothesis-testing. Examples of the procedure for selected tests follow, illustrating statistical method in practice. The purpose of each test is summarized and a classification chart identifies their interconnections and contexts of use. The bulk of the book consists of clear, concise outlines of the objective, method, strengths and limitations of each test, giving sample data. All the relevant tables of critical values are included. 100 Statistical Tests is an invaluable addition to the bookshelf of anyone working with applied statistics and quantitative methodologies throughout the social sciences, business and management.

This Book Provides Many Kinds Of Statistical Tests Available In Statistics, Which Are Widely Used In Various Disciplines, Especially Very Much Useful For The Researchers Who Need Statistical Tools And Techniques For Their Data Analysis. This Book Will Help Them To Interpret Their Data Themselves In A Better Manner. In This Book, Frequently Used Statistical Tests Are Presented In A Simple And Understandable Way With Real Life Examples And Exercises.

Nonparametric Statistical Tests: A Computational Approach describes classical nonparametric tests, as well as novel and little-known methods such as the Baumgartner-Weiss-Schindler and the Cucconi tests. The book presents SAS and R programs, allowing readers to carry out the different statistical methods, such as permutation and bootstrap tests. Th

The second edition of this text is an introduction to the use of statistical tests in psychology experiments: statistics without panic. Presented in a new textbook format, its key objective is to enable students to select appropriate statistical tests to evaluate the significance of data obtained from psychological experiments. Improvements ion the organization of chapters emphasize even more clearly the principle of introducing complex experimental designs on a need to know basis, leaving more space for an extended interpretation of analysis of variance. In an important development for the second edition, students are introduced to modern statistical packages as a useful tool for calculations, the emphasis being on understanding and interpretation.

How Many Subjects? is a practical guide to sample size calculations and general principles of cost-effective research. It introduces a simple technique of statistical power analysis which allows researchers to compute approximate sample sizes and power for a wide variety of research designs. Because the same technique is used with only slight modifications for different statistical tests, researchers can easily compare the sample sizes required by different designs and tests to make cost-effective decisions in planning a study. These comparisons, emphasized throughout the book, demonstrate important principles of design, measurement and analysis that are rarely discussed in courses or textbooks.