Suchergebnisse

Getting started -- PCA with more than two variables -- Scaling of data -- Inferential procedures -- Putting it all together -- hearing loss I -- Operations with group data -- Vector interpretation I: simplifications and inferential techniques -- Vector interpretation II: rotation -- A case history-hearing loss II -- Singular value decomposition: multidimensional scaling I -- Distance models: multidimensional scaling II -- Linear models I: regression; PCA of predictor Variables -- Linear models II: analysis of variance; PCA of response variables -- Other applications of PCA -- Flatland: special procedures for two dimensions -- Odds and ends -- What is factor analysis anyhow? -- Other competitors.

This book contains 30 selected, refereed papers from an in- ternational conference on bootstrapping and related techni- ques held in Trier 1990. Thepurpose of the book is to in- form about recent research in the area of bootstrap, jack- knife and Monte Carlo Tests. Addressing the novice and the expert it covers as well theoretical as practical aspects of these statistical techniques. Potential users in different disciplines as biometry, epidemiology, computer science, economics and sociology but also theoretical researchers s- hould consult the book to be informed on the state of the art in this area

Mit der Version 6.01 von SPSS für Windows steht das weltweit verbreitetste und mächtige Datenanalysesystem mit zahlreichen Erweiterungen und Verbesserungen nun auch unter einer deutschen Windows-Oberfläche zur Verfügung. Die Autoren, die in Lehre und Forschung langjährige Erfahrungen mit SPSS haben, bieten dem Anfänger eine Einführung und dem erfahrenen SPSS-Anwender eine umfassende Behandlung des Basissystems von SPSS für Windows 6.01. Alle Anwendungen werden ausführlich mit Beispielen aus der Praxis dargestellt. Dabei werden auch die statistischen Methoden und Verfahren mit ihren Anwendungsvoraussetzungen behandelt. Im Anhang aufgeführte Daten ermöglichen es, die meisten Anwendungen am PC nachzuvollziehen

Dieses Lehrbuch gibt einen umfassenden Überblick über Methoden der deskriptiven Statistik, die durch einige Verfahren der explorativen Datenanalyse ergänzt wurden. Die zahlreichen statistischen Möglichkeiten zur Quantifizierung empirischer Phänomene werden problemorientiert dargestellt, wobei ihre Entwicklung schrittweise erfolgt, so daß Notwendigkeit und Nutzen der Vorgehensweise deutlich hervortreten. Dadurch soll ein fundiertes Verständnis für statistische Methoden geweckt werden. Dieses wird durch repräsentative Beispiele unterstützt. Übungsaufgaben mit Lösungen ergänzen den Text

Explains how Hilbert space techniques cross the boundaries into the foundations of probability and statistics. Focuses on the theory of martingales stochastic integration, interpolation and density estimation. Includes a copious amount of problems and examples.

The subject of this book is the incorporation and integration of mathematical and statistical techniques and information science topics into the field of classification, data analysis, and knowledge organization. Readers will find survey papers as well as research papers and reports on newest results. The papers are a combination of theoretical issues and applications in special fields: Spatial Data Analysis, Economics, Medicine, Biology, and Linguistics

I: Deskriptive Statistik -- 1. Einführung -- 2. Eindimensionale Häufigkeitsverteilungen -- 3. Zweidimensionale Häufigkeitsverteilungen -- 4. Maßzahlen für eindimensionale Verteilungen -- 5. Maßzahlen für mehrdimensionale Verteilungen -- 6. Die Lorenzkurve -- II: Wahrscheinlichkeitsrechnung -- 7. Grundbegriffe der Wahrscheinlichkeitsrechnung -- 8. Diskrete Wahrscheinlichkeitsverteilungen -- 9. Stetige Wahrscheinlichkeitsverteilungen -- 10. Parameter von Wahrscheinlichkeitsverteilungen -- III: Mathematische Statistik -- 11. Relative Häufigkeiten -- 12. Die Parameter der Normalverteilung -- 13. Verteilungsunabhängige Verfahren -- 14. Der Chi-Quadrat-Test -- 15. Regressionsrechnung -- Tabellen -- Tabelle 1: Dichte der hypergeometrischen Verteilung -- Tabelle 2: Dichte der Binomial-Verteilung -- Tabelle 3: Verteilungsfunktion der Binomial-Verteilung -- Tabelle 4: Dichte der Poisson-Verteilung -- Tabelle 5: Verteilungsfunktion der Poisson-Verteilung -- Tabelle 6: Verteilungsfunktion der Standard-Normalverteilung -- Tabelle 7: Fraktile der Student-Verteilung -- Tabelle 8: Fraktile der Chi-Quadrat-Verteilung -- Tabelle 9: Fraktile der F-Verteilung -- Nomogramm zur Bestimmung von Vertrauensschranken für den Anteil p in der Grundgesamtheit -- Literatur.

AbstractThere are some kinds of violent conflicts between factions in which one generation of belligerents trains a successive generation to continue and/ or enlarge the scale of conflict in an arena where the hostilities are internecine A model is developed of the devolution of internecine conflict using the lexicon of game theory and the simple mathematics of probability Assumptions pertaining to the behavior and attitudes of factions are transcribed into mathematics to formulate a theory of conflict resolution The theory is general enough to be applied to the struggles in the Middle East as well as to warfare among youth gangs The chief proposition to emerge from the analysis demonstrates how the statistical incidence of aggressive and peaceable factions varies over time The time path has the characteristics of a stochastic process with estimable parameters

Transform methods, together with the fast Fourier transform algorithm, can be used to compute various quantities of interest in risk theory and insurance mathematics. These include the total claim size distribution at a fixed time, the mean and variance of the claim size process as a function of time in the Sparre‐Andersen model, and the probability of ruin. The associated discretization error can be reduced by applying Richardson's deferred approach to the limit. A theorem is given that puts the use of this technique on a mathematical basis in the context of compound distributions.

Sequential Stochastic Optimization provides mathematicians and applied researchers with a well-developed framework in which stochastic optimization problems can be formulated and solved. Offering much material that is either new or has never before appeared in book form, it lucidly presents a unified theory of optimal stopping and optimal sequential control of stochastic processes. This book has been carefully organized so that little prior knowledge of the subject is assumed; its only prerequisites are a standard graduate course in probability theory and some familiarity with discrete-paramet.

The article sketches the evolution of mathematical social sciences in Great Britain, focussing on Political Economy and Social Statistics. The formal methods which were later to become of greatest importance in these sciences (differential calculus and probability theory) were mainly imported from continental mathematics at the beginning of the 19th century. The emergence of Political Economy and the transformation of classical Political Arithmetic into Statistics roughly coincided with this "catching-up" process. Moreover, the "Cambridge Network of Scientists" (Cannon), with its protagonists Whewell, Herschel, Babbage and Peacock, played a central role in the adoption of French mathematics as well as in the early attempts to place the social sciences on a methodologically sound basis. Not surprisingly, the Cambridge Scientists (gathered mainly in the Cambridge Philosophical Society and the Cambridge Astronomical Society) were among the first to use mathematical methods in dealing with "the complicated conduct of our social and moral relations" (Herschel). However, the mathematicization of the social sciences cannot be seen as a smooth, continuous process of successively applying formal techniques to social phenomena. The application of the general equilibrium framework of analytical mechanics to the study of man's desires and actions, and the use of probability theory in explaining (not just describing) the synthesis and development of social aggregates, required an essential precondition: a new kind of analysis of "man", such as had emerged in geology and physiology since the late 1830s. Using the principles of natural selection and reflex action, it became possible to view human societies simultaneously as random samples and systems of forces, to which mathematical techniques now became reasonably applicable. The rise of Economics and Eugenics (founded by Jevons and Galton, respectively) towards the end of the 19th century can thus be perceived as a late consequence of this "anthropological turn". Therefore, the evolution of mathematical social sciences is not a symptom of a "mechanistic" view of man (usually associated with Cartesian epistomology), but simply another result of the very dissolving of classical "mathesis" (Foucault), which entailed the appearance of "man" as a privileged object of knowledge. ; The article sketches the evolution of mathematical social sciences in Great Britain, focussing on Political Economy and Social Statistics. The formal methods which were later to become of greatest importance in these sciences (differential calculus and probability theory) were mainly imported from continental mathematics at the beginning of the 19th century. The emergence of Political Economy and the transformation of classical Political Arithmetic into Statistics roughly coincided with this "catching-up" process. Moreover, the "Cambridge Network of Scientists" (Cannon), with its protagonists Whewell, Herschel, Babbage and Peacock, played a central role in the adoption of French mathematics as well as in the early attempts to place the social sciences on a methodologically sound basis. Not surprisingly, the Cambridge Scientists (gathered mainly in the Cambridge Philosophical Society and the Cambridge Astronomical Society) were among the first to use mathematical methods in dealing with "the complicated conduct of our social and moral relations" (Herschel). However, the mathematicization of the social sciences cannot be seen as a smooth, continuous process of successively applying formal techniques to social phenomena. The application of the general equilibrium framework of analytical mechanics to the study of man's desires and actions, and the use of probability theory in explaining (not just describing) the synthesis and development of social aggregates, required an essential precondition: a new kind of analysis of "man", such as had emerged in geology and physiology since the late 1830s. Using the principles of natural selection and reflex action, it became possible to view human societies simultaneously as random samples and systems of forces, to which mathematical techniques now became reasonably applicable. The rise of Economics and Eugenics (founded by Jevons and Galton, respectively) towards the end of the 19th century can thus be perceived as a late consequence of this "anthropological turn". Therefore, the evolution of mathematical social sciences is not a symptom of a "mechanistic" view of man (usually associated with Cartesian epistomology), but simply another result of the very dissolving of classical "mathesis" (Foucault), which entailed the appearance of "man" as a privileged object of knowledge.