This book deals with the use of Statistics in the Social Sciences and particularly in the Behavioral Sciences. Research activity in these sciences relies on the breadth of Statistical and Metric Theory, as well as the ever-growing multitude of statistical methods-applications of this theory.

The theoretical parts of this book cover the main axes in Descriptive and Inferential Statistics, as well as the basic principles of Psychometrics. These parts are developed at levels, so that they are useful both for novice researchers by providing basic guidance in statistical analysis, and for experienced statistical analysts, further explaining specific issues and techniques of statistical information processing.

Another Statistics book, then? No, because in this book, the theory is applied through Computational Algorithms that are available in the form of a CD and which the researcher is able to use for every statistical method included in the book, in order to analyze their own research data accordingly.

Specifically, on the accompanying CD, the restless scientist will find and use, through Microsoft Excel, a series of 'ready-made' statistical procedures. By inputting their research data, they will receive answers to research questions in pedagogy-education, psychology, sociology, and other Social Sciences, regarding the main axes of basic univariate statistical analysis.

The included statistical algorithms have been specially created in combination with the contents of the book. Together, they constitute standalone software for basic univariate statistical information processing, ranging from simple frequency distributions and various correlation coefficients to two-way analysis of variance with unequal samples and mixed models in this analysis.

By analyzing research data through this software, the student is enabled to familiarize themselves with the basic statistical theory and also to apply it in their research work while learning, while the more experienced researcher will certainly use the appropriate statistical techniques to answer fundamental research questions without being obliged to learn and costly use of any particularly specialized statistical 'package'.

Perhaps the most important feature of the algorithms included in this book is that, regardless of experience, any social scientist, following the logic of computational functions as it appears in the computational cells within Excel files, will be able to create their own statistical processing algorithms, depending on their specific research and statistical needs.

[Excerpt from the text on the back cover of the edition]