Average Reviews:
(More customer reviews)I am currently a first-year graduate student in the Experimental Psychology track, but I was still an undergrad when I started using Dr. Grice's program. I found it easy to understand and work with and have since used it for presentations in my advanced statistics class. I am currently working with my mentor on a paper which used Observation Oriented Modeling to analyze data from many experiments and create a new perspective on the topic.
I think that this book has been useful in allowing me as a growing student to expand my perspective on statistics, the way we view cause and effect, and the many different ways that are still to be seen.
I would recommend this book to anyone who wishes to further their knowledge of statistics, experience a novel view of cause in behavioral sciences, or even just run some interesting analyses and gain insight into their data.
Click Here to see more reviews about: Observation Oriented Modeling: Analysis of Cause in the Behavioral Sciences (Elsevier Science & Technology Books)
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 that has been written to accompany the book and will be provided free to book buyers on an accompanying website.
The software has a user-friendly interface, similar to SPSS and SAS , which are the two most commonly used software analysis packages, and the analysis options are flexible enough to replace numerous traditional techniques such as t-tests, ANOVA, correlation, multiple regression, mediation analysis, chi-square tests, factor analysis, and inter-rater reliability. The output and graphs generated by the software are also easy to interpret, and all effect sizes are presented in a common metric; namely, the number of observations correctly classified by the algorithm. The software is designed so that undergraduate students in psychology will have no difficulty learning how to use the software and interpreting the results of the analyses.
* Describes the problems that statistics are meant to answer, why popularly used statistics often fail to fully answer the question, and how OOM overcomes these obstacles * Chapters include examples of statistical analysis using OOM * Software for OOM comes free with the book * Accompanying websiteinclude svideo instruction on OOM use
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