Statistical Methods [antikvár]

Preface A note to the instructor In most disciplines, including business and economics, there is an increasing awareness of the need to comprehend basic statistical methodology and its language for successful careers in industry, government, and self-em-ployed positions. Today, with the widespread use of computers (mainframes and now microcomputers), the collection and analysis of data for decision making are, for many enterprises, essential activities for efficient operations. In a typical organization, perhaps only a few individuals are directly involved in the collection, tabulation, and the analysis of data, but many others must have a sufficient understanding of statistics to interpret the analyses in order to make reasonable and timely decisions. Because statistical methods are now a part of numerous non-mathematics curricula, it is no longer possible, or indeed appropriate, to assume that students who study introductory statistics are well trained mathematically. The demand for statistical training has increased so dramatically in the past several years and has affected so many disciplines that most introductory courses cannot require more than a knowledge of algebra on the part of the student. We believe that most students taking an introductory course do not require the level of knowledge that would enable them to pursue training for a career in statistics. Rather, they need to understand the fundamental ideas of statistical analysis presented in a competent but not necessarily mathematically rigorous fashion. This is the essential characteristic of this text. By suggesting the potential importance that statistical analysis has in various careers, we hope to further motivate students in their study of statistics. Furthermore, we have emphasized the development of the logic of statistical