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SummaryThe paper deals with the concept of identification in inferential statistics. At first a general concept of identification is defined and developed. Thereafter, the general theory is applied to univariate linear regression and simultaneous equation systems. Finally, attention is paid to models with lagged variables and some new related problems are suggested.

THIS PAPER ATTEMPTS TO EQUIP CONTEXTUAL RESEARCHERS WITH A NECESSARY UNDERSTANDING OF THE MAIN STATISTICAL ISSUES INVOLVED IN CONTEXTUAL ANALYSIS. AFTER OUTLINING THE BASIC PROBLEMS OF STATISTICAL INFERENCE, THE PAPER PROVIDES AN EMPIRICAL EXAMPLE THAT SHOWS STRONG CONTEXTUAL EFFECTS.

"This book is essentially a non-mathematical exposition of the theory of statistics written for experimental scientists. It is an expanded version of lecture notes used for a one-year course in statistics taught at Oregon State College since 1949. My intention in this book is to stress a few basic principles of statistical inference and prepare the student to study a special branch of statistics, such as the design of experiments, the sampling survey, and quality control. I have not attempted a comprehensive treatment of the subject. The descriptive statistics is only briefly presented in Chapter 2. Students in the experimental sciences are accustomed to acquiring knowledge through experiments, that is, through induction. It is fitting, therefore, that these students should acquire an understanding of statistics by experimental, or inductive, means rather than by mathematical, or deductive, means. Examples are used to illustrate the possible applications of the principles presented. The book is roughly divided into three parts by the two review chapters, 13 and 20. The first part is devoted to the basic concept of statistical inference and to the introduction of the four distributions. The second part is devoted essentially to the analysis of variance, and the third part to the non-parametric methods. These topics are joined, however, by repeated references to the analysis of variance. The importance of the individual degree of freedom is stressed"--Preface. (PsycINFO Database Record (c) 2008 APA, all rights reserved).