Empirical Direction in Design and Analysis

By Norman H. Anderson

The goal of Norman H. Anderson's new book is to help students develop skills of scientific inference. To accomplish this he organized the book around the "Experimental Pyramid"--six levels that represent a hierarchy of considerations in empirical investigation--conceptual framework, phenomena, behavior, measurement, design, and statistical inference. To facilitate conceptual and empirical understanding, Anderson de-emphasizes computational formulas and null hypothesis testing. Other features include:
*emphasis on visual inspection as a basic skill in experimental analysis to help students develop an intuitive appreciation of data patterns;
*exercises that emphasize development of conceptual and empirical application of methods of design and analysis and de-emphasize formulas and calculations; and
*heavier emphasis on confidence intervals than significance tests.

The book is intended for use in graduate-level experimental design/research methods or statistics courses in psychology, education, and other applied social sciences, as well as a professional resource for active researchers. The first 12 chapters present the core concepts graduate students must understand. The next nine chapters serve as a reference handbook by focusing on specialized topics with a minimum of technicalities.

• Format: Hardcover
• Language: English
• ISBN: 080583978X
• ISBN13: 9780805839784
• Release Date: July 2001
• Publisher: Psychology Press
• Length: 880 Pages
• Weight: 3.00 lbs.
• Dimensions: 1.7" x 6.2" x 9.1"

Customer Reviews

Super!

This text is terrific. it is clear and easy to read, and emphasizes the practical aspects of analysis. It would be very useful for both students and researchers. It contains detailed explanations of both the standard techniques and many of the less common analyses as well.

Using Anderson's "Empirical Direction in Design and Analysis

Professor Norman Anderson is widely recognized as a leading psychological scientist. In this huge book he details an approach to scientific experimentation developed during his nearly 50 years of research and mathematical modeling. The interpretation of results is paramount. In this regard, a most distinctive feature is the note section at the end of each chapter. Many "notes" reveal misinterpretations of published scientific experiments. Statistical analysis is the application of mathematical models to data. Anderson illustrates this application across a variety of statistical models including analysis of variance, covariance, regression. Many numerical examples, and an average of 22 multi-part problems at the end of chapters, provide for an in-depth understanding of data analysis. A terrific book for those who need to design experiments and interpret their results.