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Dieses Lehrbuch bietet dem Leser - dem Studierenden und dem praktischen Anwender der Statistik - eine übersichtliche und umfassende Einführung in die statistische Methodenlehre und in die Datenanalyse mit EXCEL und SPSS. Die statistischen Methoden sind mit konkreten Berechnungsbeispielen und zahlreichen grafischen Darstellungen anschaulich beschrieben. Zu Beginn jedes Kapitels bereiten Leitfragen das aktive Erlernen der Formeln und Methoden vor. Ein Master-Projekt, das die einzelnen Kapitel und Abschnitte in Form von Berechnungsbeispielen wie ein roter Faden durchläuft, verdeutlicht Ziele, Inhalt und praktische Anwendung der statistischen Methoden. Die zahlreichen Erläuterungen und Hinweise zum Einsatz von EXCEL und SPSS erleichtern den Zugang zur Statistik. Zur Anwendung und Vertiefung der statistischen Methoden ist - in Ergänzung zu diesem Lehrbuch - ebenfalls bei Oldenbourg das Übungsbuch "Statistik verstehen mit Excel - Interaktiv lernen und anwenden" mit kostenlosen Downloads (siehe www.oldenbourg.de) erschienen.
Statistics. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics
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In bewährter Weise werden in diesem Lehrbuch grundlegende Begriffe und Verfahren in der Statistik durch Beispiele erläutert und können anhand von Aufgaben zur Selbstkontrolle erprobt werden. Entsprechende Lösungen sind separat am Ende des Buches zu finden. Der Lehrbuchinhalt umfasst die deskriptive Statistik, die Wahrscheinlichkeitsrechnung und die induktive Statistik. Darüber hinaus geben die Autoren einen Ausblick auf weitere wichtige Teilgebiete der Statistik wie etwa Prognoserechnung, Ökonometrie, multivariate Verfahren, statistische Entscheidungstheorie und statistische Software. Zur Lektüre dieses einführenden Werks sind die Vorkenntnisse in mathematischer Propädeutik ausreichend, die in allen wirtschafts- und sozialwissenschaftlichen Fakultäten im Grundstudium vermittelt werden.
Statistics. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics
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Mathematics --- Statistics --- Computer science --- Computer science. --- Mathematics. --- Statistics. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Math --- Informatics --- Econometrics --- Science
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Statistics. --- Engineering --- Statistical methods. --- Statistics --- Statistical methods --- Engineering statistics --- Engineering mathematics --- Statistical analysis --- Statistical data --- Statistical science --- Mathematics --- Econometrics
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Dieses Lehrbuch enthält das komplette Statistikwissen, das für ein Studium benötigt wird: beschreibende Statistik, Wahrscheinlichkeitsrechnung und die statistische Inferenz. In der beschreibenden Statistik wird gezeigt, wie man umfangreiche Datensätze übersichtlich durch Abbildungen und Parameter darstellen kann. Hierzu gehören auch die Beschreibung von Zusammenhängen zwischen Merkmalen und die Regression. Die Wahrscheinlichkeitsrechnung ist kein Selbstzweck, sondern wird für die statistische Inferenz gebraucht. Dort wird die Information einer Stichprobe mit Hilfe von Wahrscheinlichkeitsaussagen auf die Grundgesamtheit übertragen. Dies erfolgt in Form von Parameterschätzungen und Hypothesentests. Zudem zeichnet sich das Buch durch einen hohen Anwendungsbezug aus. So sind die Übungsaufgaben am Ende eines Kapitels, welche der Festigung des Lernstoffs dienen, nicht konstruiert, sondern behandeln konkrete Fragestellungen einer fiktiven Firma. Die Lösungen der Aufgaben sind nur online über das Downloadportal des Verlages verfügbar.
Commercial statistics --- Statistics. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Business --- Business statistics --- Commerce --- Statistics --- Methodology.
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Statistics --- Estadística. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Yearbooks. --- América Latina.
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Astronomy needs statistical methods to interpret data, but statistics is a many-faceted subject that is difficult for non-specialists to access. This handbook helps astronomers analyze the complex data and models of modern astronomy. This second edition has been revised to feature many more examples using Monte Carlo simulations, and now also includes Bayesian inference, Bayes factors and Markov chain Monte Carlo integration. Chapters cover basic probability, correlation analysis, hypothesis testing, Bayesian modelling, time series analysis, luminosity functions and clustering. Exercises at the end of each chapter guide readers through the techniques and tests necessary for most observational investigations. The data tables, solutions to problems, and other resources are available online at www.cambridge.org/9780521732499. Bringing together the most relevant statistical and probabilistic techniques for use in observational astronomy, this handbook is a practical manual for advanced undergraduate and graduate students and professional astronomers.
Statistical astronomy --- Statistique stellaire --- Statistical astronomy. --- Statistics. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Astronomy --- Stellar statistics --- Mathematical statistics
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Il volume contiene in forma compatta il programma svolto negli insegnamenti introduttivi di statistica e tratta alcuni argomenti indispensabili per l'attività di ricerca, come ad esempio i metodi di simulazione Monte Carlo, le procedure di minimizzazione e le tecniche di analisi dei dati di laboratorio. Gli argomenti vengono sviluppati partendo dai fondamenti, evidenziandone gli aspetti applicativi, fino alla descrizione dettagliata di molti casi di particolare rilevanza in ambito scientifico e tecnico. Numerosi esempi ed esercizi risolti valorizzano l'opera ed aiutano il lettore nella comprensione dei punti più difficili ed importanti. Come ulteriore supporto, questa terza edizione contiene molti programmi applicativi scritti col software libero Scilab, scaricabili dal sito web creato dagli autori. Il testo è rivolto agli studenti universitari dei corsi ad indirizzo scientifico e a tutti quei ricercatori che devono risolvere problemi concreti che coinvolgono aspetti statistici e di simulazione. .
Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Statistics. --- Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics --- Statistics .
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"This book offers a practical, concise introduction to regression analysis for upper-level undergraduate students of diverse disciplines including, but not limited to statistics, the social and behavioral sciences, MBA, and vocational studies. The book's overall approach is strongly based on an abundant use of illustrations, examples, case studies, and graphics. It emphasizes major statistical software packages, including SPSS(r), Minitab(r), SAS(r), R, and R/S-PLUS(r). Detailed instructions for use of these packages, as well as for Microsoft Office Excel(r), are provided on a specially prepared and maintained author web site. Select software output appears throughout the text. To help readers understand, analyze, and interpret data and make informed decisions in uncertain settings, many of the examples and problems use real-life situations and settings. The book introduces modeling extensions that illustrate more advanced regression techniques, including logistic regression, Poisson regression, discrete choice models, multilevel models, Bayesian modeling, and time series and forecasting. New to this edition are more exercises, simplification of tedious topics (such as checking regression assumptions and model building), elimination of repetition, and inclusion of additional topics (such as variable selection methods, further regression diagnostic tests, and autocorrelation tests)"--
Regression analysis --- Statistics --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling
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The text gives a concise introduction into fundamental concepts in statistics. Chapter 1: Short exposition of probability theory, using generic examples. Chapter 2: Estimation in theory and practice, using biologically motivated examples. Maximum-likelihood estimation in covered, including Fisher information and power computations. Methods for calculating confidence intervals and robust alternatives to standard estimators are given. Chapter 3: Hypothesis testing with emphasis on concepts, particularly type-I , type-II errors, and interpreting test results. Several examples are provided. T-tests are used throughout, followed important other tests and robust/nonparametric alternatives. Multiple testing is discussed in more depth, and combination of independent tests is explained. Chapter 4: Linear regression, with computations solely based on R. Multiple group comparisons with ANOVA are covered together with linear contrasts, again using R for computations.
Statistics. --- Statistics --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Statistics, general. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Econometrics --- Statistics .
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