Statistics and Measurement Concepts with OpenStat, 2013

This reference manual for the OpenStat software, an open-source software developed by William Miller, covers a broad spectrum of statistical methods and techniques.  A unique feature is its compatibility with many other statistical programs. OpenStat users are researchers and students in the social sciences, education, or psychology, who benefit from the hands on approach to Statistics. During and upon completion of courses in Statistics or measurement, students and future researchers need a low cost computer program available to them, and OpenStat fills this void. The software is used in Statistics courses around the world with over 50,000 downloads per year. The manual covers all functions of the OpenStat software, including measurement,  ANOVAS, regression analyses, simulations, product-moment and partial correlations, and logistic regression. The manual is an important learning tool that explains the Statistics behind the many analyses possible with the program and demonstrates these analyses.

William Miller has a diverse background in Industrial Technology, Psychology, Statistics and Measurement.  He has taught courses in Electronics, computer programming, educational psychology, measurement and statistics and published many articles in these subject areas  He has taught statistics for over 30 years and developed a number of statistical packages for free use by educators and researchers in a variety of fields including education, psychology, medicine, economics and geology.  He received his PhD. from the University of Iowa in Educational Psychology, Statistics and Measurement.  His academic experiences include director of two university computing centers, director of a counseling center and assistant to a university president for information services in addition to his teaching.

Provides fundamental guidance to novice students on basic statistical principles and methods through utilizing the OpenStat software

The second half of the book delves into a large number of common analysis methods, ranging from the basic descriptives (e.g., means, frequencies and crosstabs) all the way through many multivariate and non parametric methods

Covers specific applications to the software in finance and neural networks/biostatistics

Contains over 160 exercises at the end of the book

Includes supplementary material: sn.pub/extras