Найти книгу: "Numerical Issues in Statistical Computing for the Social Scientist"

At last—a social scientist's guide through the pitfalls of modern statistical computing Addressing the current deficiency in the literature on statistical methods as they apply to the social and behavioral sciences, Numerical Issues in Statistical Computing for the Social Scientist seeks to provide readers with a unique practical guidebook to the numerical methods underlying computerized statistical calculations specific to these fields. The authors demonstrate that knowledge of these numerical methods and how they are used in statistical packages is essential for making accurate inferences. With the aid of key contributors from both the social and behavioral sciences, the authors have assembled a rich set of interrelated chapters designed to guide empirical social scientists through the potential minefield of modern statistical computing. Uniquely accessible and abounding in modern-day tools, tricks, and advice, the text successfully bridges the gap between the current level of social science methodology and the more sophisticated technical coverage usually associated with the statistical field. Highlights include: A focus on problems occurring in maximum likelihood estimation Integrated examples of statistical computing (using software packages such as the SAS, Gauss, Splus, R, Stata, LIMDEP, SPSS, WinBUGS, and MATLAB®) A guide to choosing accurate statistical packages Discussions of a multitude of computationally intensive statistical approaches such as ecological inference, Markov chain Monte Carlo, and spatial regression analysis Emphasis on specific numerical problems, statistical procedures, and their applications in the field Replications and re-analysis of published social science research, using innovative numerical methods Key numerical estimation issues along with the means of avoiding common pitfalls A related Web site includes test data for use in demonstrating numerical problems, code for applying the original methods described in the book, and an online bibliography of Web resources for the statistical computation Designed as an independent research tool, a professional reference, or a classroom supplement, the book presents a well-thought-out treatment of a complex and multifaceted field.

Although new ventures’ competitive positioning and their founders’ social networks are both recognized as important in the context of transition economies, not much is known about their multiplicative effect on performance. We build on the strategic management literature and social network theory to develop theoretical predictions about the role of competitive strategies and social capital for entrepreneurial performance. These are tested with survey data from Bulgaria. We find that both the venture’s competitive strategic positioning and the founder’s networking positively influence performance. The hypothesized moderating effect of networking for the relationship between differentiation strategy and performance received only tentative support. Contrary to expectations, we find a negative moderating effect of networking for the relationship of cost leadership with performance. These results suggest that the entrepreneur’s network plays a role in shaping how strategies influence performance by possibly upholding differentiation and deemphasizing cost leadership strategy. Implications for managerial practice and public policy are discussed.

Полный вариант заголовка: «Theorie des richesses sociales : Tome 1 : suivie d'une bibliographie de l'economie politique / par le Comte Frederic Skarbek».

Полный вариант заголовка: «Theorie des lois sociales / par J.F. Dauray de Brie».

Полный вариант заголовка: «Theorie des richesses sociales : Tome 2 : suivie d'une bibliographie de l'economie politique / par le Comte Frederic Skarbek».

Полный вариант заголовка: «Histoire de la Sorbonne dans laquelle on voit l'insluence de la Theologie sur l'ordre social. T. 1 / par M. l'Abbe J. Duvernet».