This book is intended for psychology majors and graduate students who are conducting experiments for the first time and are faced with the task of making sense out of their data. This much needed "how-to-do-it" text illustrates the application of statistical methods to the data from small samples. It also serves as a handbook, with twenty-two tables presented at the end of the text that will allow the student to carry out virtually every computation necessary in analyzing his data. Almost all of the examples and illustrations are drawn from actual experiments so that the student can see how professional scientists examine their data. The book also shows students the kinds of data that are encountered in psychological research, the kinds of questions investigators seek to answer, and how these questions are approached.
The author asserts that statistics is not an abstract discipline but a tool in research. However, the book also imparts a philosophy of data analysis and its meaning, a concern for questions of the function of data analysis and the interpretations that legitimately can be drawn from data. In brief, Data Analysis asks: What kinds of data are met in psychological research? What can we do with these data? What can we conclude as a result of this doing?
The book will be invaluable for students who, even though they may have taken a previous statistics course, are still unsure of what statistical techniques should be used in interpreting their data.
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Maße
Höhe: 229 mm
Breite: 152 mm
Dicke: 16 mm
Gewicht
ISBN-13
978-0-202-30900-2 (9780202309002)
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Schweitzer Klassifikation
Edward L. Wike was educated at the University of California at Los Angeles, where he received his Ph.D. in experimental psychology in 1952. He has contributed many articles to psychology journals and is currently Professor of Psychology, University of Kansas. He was a member of American Psychology Association, Sigma Xi, as well as the Psychonomic Society. He was named Outstanding Educator in America in 1975.
Preface 1. Opening Shots 2. The Search for Indications 3. Steps to Inference: I. Numbers 4. Steps to Inference: II. Ranks and Signs 5. Steps to Inference: III. Classes 6. Steps to Inference: IV. Relationships 7. Closing Shots; Testing Statistical Hypotheses vs. Confidence Intervals - Multiple-Analysis Revisited - Some Tactics for Research and Data Analysis - Final Remarks; Answers to the Even-Numbered Problems
