This book introduces a new data analysis technique that addresses long standing criticisms of the current standard statistics. Observation Oriented Modelling presents the mathematics and techniques underlying the new method, discussing causality, modelling, and logical hypothesis testing. Examples of how to approach and interpret data using OOM are presented throughout the book, including analysis of several classic studies in psychology. These analyses are conducted using comprehensive software for the Windows operating system.
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Traditional methods of data analysis in psychology have long been criticized by scientists and philosophers, the American Psychological Association, and the National Institute for Mental Health. However up to now, no reasonable alternative had been presented. Observation Oriented Modeling (OOM) changes that. OOM is not just another statistical or data analysis methodology that relies upon effect sizes, p levels, or r-squares, but rather a straightforward evaluation of the precise consequences specified by a theory or hypothesis. OOM develops integrated models to accurately explain patterns of observation.
Observation Oriented Modeling introduces this new methodology, what it is and does to advance psychology as a science. Numerous examples are presented of how to interpret data using OOM.
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