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This second edition is still designed for graduate students and researchers in the social, behavioral and health sciences who have modest backgrounds in mathematics and statistics. Also, priority is still given to the discussion of seminal ideas that underlie the analysis of variance. With respect to the first edition, the late Jum C. Nunnally of Vanderbilt University remarked, 'Overall, there is no better text on statistics in the behavioral sciences available, and I strongly recommend it.' A new feature is the optional availability of a microcomputer software package, MICRO-ANOVA, that will enable researchers to perform all analyses presented in the text on IBM PCs or equivalent computers. The software package is available through UPA.
Experimental Design: Procedures for Behavioral Sciences, Fourth Edition is a classic text with a reputuation for accessibility and readability. It has been revised and updated to make learning design concepts even easier. Roger E. Kirk shows how three simple experimental designs can be combined to form a variety of complex designs. He provides diagrams illustrating how subjects are assigned to treatments and treatment combinations. New terms are emphasized in boldface type, there are summaries of the advantages and disadvantages of each design, and real-life examples show how the designs are used.
The Book Has Been Addressed To The Students And Researchers In The Disciplines Of Psychology, Education, Sociology, Social-Work, Medicine, Management, And Allied Disciplines. It Has Been Written For Those Who Do Not Possess Sophisticated Mathematical Background. Various Designs And Their Analyses Have Been Presented In Simple Understandable Language. The Intended Emphasis Is To Make The Reader Understand The Basic Principles Of Experimental Design, Layout For Data Collection, Analysis Of Data, Interpretation Of Results Of Experimental Outcome. It Offers An Integrated Approach Placing Due Emphasis On Theory, Application, And Computational Procedures. Schematic Representations Of Analysis For Each Design Is A Novel Feature Of This Book, It Makes The Analysis Simple And Easy To Comprehend. Each Design Includes General Layout For Data Collection, Schematic Representation Of The Analysis, Followed By Numerical Example With Detailed Solution And Interpretation. Numerous Illustrations, Many From Published Research, Are Provided With The Intent To Equip The Reader To Develop Insight Into The Intricacies Of Research Strategy. Special Treatment Has Been Given To Within Subject And Mixed Designs. Multivariate Analysis Of Variance, Analysis Of Covariance, And Also Analysis Of Variance By Ranks Have Been Included.
Scientists planning experiments in medical and behavioral research will find this handbook and dictionary an invaluable desk reference tool. Also recommended as a textbook for students of Experimental Design or accompanying courses in Statistics. Principles of experimental design are introduced, techniques of experimental design are described, and advantages and disadvantages of often used designs are discussed. This two-part volume, a handbook of experimental design and a dictionary providing short explanations for many terms related to experimental design, contains information that will not quickly become outdated.
A complete course in data collection and analysis for students who need to go beyond the basics. A true course companion, the engaging writing style takes readers through challenging topics, blending examples and exercises with careful explanations and custom-drawn figures ensuring the most daunting concepts can be fully understood.
Starting with the premise that all behavioral research is an effort to understand behavioral variability (variability in behavior across situations, among individuals, and over time), Introduction to Behavioral Research Methods shows readers how to conceptualize questions, measure variables, design studies, and analyze data in order to understand variability in behavior, thought, and emotion. After chapters that introduce behavioral science, the central role of variability in the research process, and measurement, the text deals with the four basic approaches to behavioral research: descriptive research, correlational research, experimental research, and quasi-experimental research. Although the focus is on research design, elementary statistical analyses (such as correlation, t-tests, and ANOVA) are introduced so that students understand statistics well enough to read research articles and to comprehend the implications of research design for the quality of the data that are collected. Chapters on research ethics and scientific writing (including the most recent version of APA style) round out the book. Throughout each chapter, boxes on "Developing Your Research Skills" and "Behavioral Research Case Study" provide practical examples and pique student interest. Feedback from instructors and students who have used previous editions of the text attest to its comprehensive coverage of research methods, its readability and student-friendly approach, and the pedagogical usefulness of the integrating theme of behavioral variability.
Oehlert's text is suitable for either a service course for non-statistics graduate students or for statistics majors. Unlike most texts for the one-term grad/upper level course on experimental design, Oehlert's new book offers a superb balance of both analysis and design, presenting three practical themes to students: • when to use various designs • how to analyze the results • how to recognize various design options Also, unlike other older texts, the book is fully oriented toward the use of statistical software in analyzing experiments.
Written for a research methods course that follows a preliminary statistics course. Author David Pittengerâ¬"s insight that students who studied statistics first had not mastered that subject lead to writing a methods text that reviews and integrates statistical discussions with that of research design. Employing an informal style with interesting everyday examples, Pittenger emphasizes that good psychological research allows us to answer many practical questions related to improving the quality of life.