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The Poisson-Dirichlet Distribution and Related Topics ab 82.49 € als pdf eBook: Models and Asymptotic Behaviors. Aus dem Bereich: eBooks, Fachthemen & Wissenschaft, Mathematik,

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Were you looking for the book with access to MyStatLab? This product is the book alone, and does NOT come with access to MyStatLab. Buy the book and access card package to save money on this resource. In Statistics for Business: Decision Making and Analysis, authors Robert Stine and Dean Foster of the University of Pennsylvania’s Wharton School, take a sophisticated approach to teaching statistics in the context of making good business decisions. The authors show students how to recognize and understand each business question, use statistical tools to do the analysis, and how to communicate their results clearly and concisely. In addition to providing cases and real data to demonstrate real business situations, this text provides resources to support understanding and engagement. A successful problem-solving framework in the 4-M Examples (Motivation, Method, Mechanics, Message) model a clear outline for solving problems, new What Do You Think questions give students an opportunity to stop and check their understanding as they read, and new learning objectives guide students through each chapter and help them to review major goals. Software Hints provide instructions for using the most up-to-date technology packages. The Second Edition also includes expanded coverage and instruction of Excel® 2010 and the XLSTAT ™ add-in. The MyStatLab™ course management system includes increased exercise coverage with the Second Edition, along with 100% of the You Do It exercises and a library of 1,000 Conceptual Questions that require students to apply their statistical understanding to conceptual business scenarios. Business Insight Videos show students how statistical methods are used by real businesses, and new StatTalk Videos present statistical concepts through a series of fun, brief, real-world examples. Technology tutorial videos at the exercise level support software use. Features + Benefits Statistics in Practice: Preparing Students for Real Business 4-M Examples (Motivation, Method, Mechanics, Message) provide a consistent methodology used for worked-out examples. This approach gives students a consistent structure for solving problems and presenting their findings in the appropriate context. Running Business Examples start each chapter by framing a business question to motivate the contents of the chapter. The example is referenced throughout the chapter when new statistical methods are presented. Statistics in Action case studies follow each of the four parts of the book. These longer applications expand on the statistical methods presented within the preceding part and use them to delve into substantive aspects of real-world business cases. Video resources available in MyStatLab offer students insight into how statistical concepts are applied in the business world and the world around us. Business Insight Videos show how statistical methods are used by real businesses. NEW! StatTalk Videos present statistical concepts through a series of fun, brief, real-world vignettes. Practice & Support: Challenging Students to Assess, Analyze and Report NEW! More than 150 exercises are new or have been updated to provide readers with the most up-to-date and relevant data available. Exercises are divided into five types. Each type focuses on a particular skill to build a deeper understanding of business statistics. Mix and Match and True/False problems test whether students recognize symbols and important steps of calculations. Think About It questions encourage students to pull together concepts and ideas from the chapter; no technology is required. You Do It problems provide practice working through the mechanics of solving a problem (statistical software usage is recommended). These exercises apply the statistical concepts students have learned in the chapter to data related to a business application. Data are available on the included CD-ROM. 4-M Questions are richer, more substantive problems that mimic real applications of statistics in business. Data are available on the included CD-ROM. Support NEW! 30 new What Do You Think? questions check students’ comprehension of the important ideas in the preceding section, ensuring that they understand the concepts before moving on in the chapter. Caution icons indicate a concept that can be troublesome and helps students avoid making common mistakes. Tip icons highlight important ideas or hints within the exposition so that readers don’t overlook them. Best Practices and Pitfalls listed at the end of every chapter offer reminders to help students avoid mistakes such as using the wrong method for a situation, or misinterpreting results. Technology Integration: Giving Students More Tools for Their Future Careers Software Hints at the end of each chapter provide relevant commands for popular statistics packages: Excel®, Minitab®, and JMP®. Extensive graphics, including Excel screenshots throughout the chapters and exercise sets, give students the opportunity to get familiar with seeing and interpreting statistical software output. Technology Tutorial Videos and Study Cards within MyStatLab provide targeted guidance to using statistical software. (Study Cards are available for bundling.) Preface Index of Application PART ONE: VARIATION 1. Introduction 1.1 What Is Statistics? 1.2 Previews 2. Data 2.1 Data Tables 2.2 Categorical and Numerical Data 2.3 Recoding and Aggregation 2.4 Time Series 2.5 Further Attributes of Data Chapter Summary 3. Describing Categorical Data 3.1 Looking at Data 3.2 Charts of Categorical Data 3.3 The Area Principle 3.4 Mode and Median Chapter Summary 4. Describing Numerical Data 4.1 Summaries of Numerical Variables 4.2 Histograms 4.3 Boxplot 4.4 Shape of a Distribution 4.5 Epilog Chapter Summary 5. Association between Categorical Variables 5.1 Contingency Tables 5.2 Lurking Variables and Simpson's Paradox 5.3 Strength of Association Chapter Summary 6. Association between Quantitative Variables 6.1 Scatterplots 6.2 Association in Scatterplots 6.3 Measuring Association 6.4 Summarizing Association with a Line 6.5 Spurious Correlation Chapter Summary Statistics in Action: Financial Time Series Statistics in Action: Executive Compensation PART TWO: PROBABILITY 7. Probability 7.1 From Data to Probability 7.2 Rules for Probability 7.3 Independent Events Chapter Summary 8. Conditional Probability 8.1 From Tables to Probabilities 8.2 Dependent Events 8.3 O rganizing Probabilities 8.4 O rder in Conditional Probabilities Chapter Summary 9. Random Variables 9.1 Random Variables 9.2 Properties of Random Variables 9.3 Properties of Expected Values 9.4 Comparing Random Variables Chapter Summary 10. Association between Random Variables 10.1 Portfolios and Random Variables 10.2 Joint Probability Distribution 10.3 Sums of Random Variables 10.4 Dependence between Random Variables 10.5 IID Random Variables 10.6 Weighted Sums Chapter Summary 11. Probability Models for Counts 11.1 Random Variables for Counts 11.2 Binomial Model 11.3 Properties of Binomial Random Variables 11.4 Poisson Model Chapter Summary 12. The Normal Probability Model 12.1 Normal Random Variable 12.2 The Normal Model 12.3 Percentiles 12.4 Departures from Normality Chapter Summary Statistics in Action: Managing Financial Risk Statistics in Action: Modeling Sampling Variation PART THREE: INFERENCE 13. Samples and Surveys 13.1 Two Surprising Properties of Samples 13.2 Variation 13.3 Alternative Sampling Methods 13.4 Questions to Ask Chapter Summary 14. Sampling Variation and Quality 14.1 Sampling Distribution of the Mean 14.2 Control Limits 14.3 Using a Control Chart 14.4 Control Charts for Variation Chapter Summary 15. Confidence Intervals 15.1 Ranges for Parameters 15.2 Confidence Interval for the Mean 15.3 Interpreting Confidence Intervals 15.4 Manipulating Confidence Intervals 15.5 Margin of Error Chapter Summary 16. Statistical Tests 16.1 Concepts of Statistical Tests 16.2 Testing the Proportion 16.3 Testing the Mean 16.4 Significance versus Importance 16.5 Confidence Interval or Test? Chapter Summary 17. Comparison 17.1 Data for Comparisons 17.2 Two-Sample z-test for Proportions 17.3 Two-Sample Confidence Interval for Proportions 17.4 Two-Sample T-test 17.5 Confidence Interval for the Difference between Means 17.6 Paired Comparisons Chapter Summary 18. Inference for Counts 18.1 Chi-Squared Tests 18.2 Test of Independence 18.3 General versus Specific Hypotheses 18.4 Tests of Goodness of Fit Chapter Summary Statistics in Action: Rare Events Statistics in Action: Data Mining Using Chi-Squared PART FOUR: REGRESSION MODELS 19. Linear Patterns 19.1 Fitting a Line to Data 19.2 Interpreting the Fitted Line 19.3 Properties of Residuals 19.4 Explaining Variation 19.5 Conditions for Simple Regression Chapter Summary 20. Curved Patterns 20.1 Detecting Nonlinear Patterns 20.2 Transformations 20.3 Reciprocal Transformation 20.4 Logarithm Transformation Chapter Summary 21. The Simple Regression Model 21.1 The Simple Regression Model 21.2 Conditions for the SRM 21.3 Inference in Regression 21.4 Prediction Intervals Chapter Summary 22. Regression Diagnostics 22.1 Changing Variation 22.2 Outliers 22.3 Dependent Errors and Time Series Chapter Summary 23. Multiple Regression 23.1 The Multiple Regression Model 23.2 Interpreting Multiple Regression 23.3 Checking Conditions 23.4 Inference in Multiple Regression 23.5 Steps in Fitting a Multiple Regression Chapter Summary 24. Building Regression Models 24.1 Identifying Explanatory Variables 24.2 Collinearity 24.3 Removing Explanatory Variables Chapter Summary 25. Categorical Explanatory Variables 25.1 Two-Sample Comparisons 25.2 Analysis of Covariance 25.3 Checking Conditions 25.4 Interactions and Inference 25.5 Regression with Several Groups Chapter Summary 26. Analysis of Variance 26.1 Comparing Several Groups 26.2 Inference in ANOVA Regression Models 26.3 Multiple Comparisons 26.4 Groups of Different Size Chapter Summary 27. Time Series 27.1 Decomposing a Time Series 27.2 Regression Models 27.3 Checking the Model Chapter Summary Statistics in Action: Analyzing Experiments Statistics in Action: Automated Modeling Appendix: Tables Answers Photo Acknowledgments Index Supplementary Material (online-only) Alternative Approaches to Inference More Regression 2-Way ANOVAWere you looking for the book with access to MyStatLab? This product is the book alone, and does NOT come with access to MyStatLab. Buy the book and access card package to save money on this resource.In Statistics for Business: Decision Making and Analysis, authors Robert Stine and Dean Foster of the University of Pennsylvania s Wharton School, take a sophisticated approach to teaching statistics in the context of making good business decisions. The authors show students how to recognize and understand each business question, use statistical tools to do the analysis, and how to communicate their results clearly and concisely.In addition to providing cases and real data to demonstrate real business situations, this text provides resources to support understanding and engagement. A successful problem-solving framework in the 4-M Examples (Motivation, Method, Mechanics, Message) model a clear outline for solving problems, new What Do You Think questions give students an opportunity to stop and check their understanding as they read, and new learning objectives guide students through each chapter and help them to review major goals. Software Hints provide instructions for using the most up-to-date technology packages. The Second Edition also includes expanded coverage and instruction of Excel® 2010 and the XLSTAT add-in.The MyStatLab course management system includes increased exercise coverage with the Second Edition, along with 100% of the You Do It exercises and a library of 1,000 Conceptual Questions that require students to apply their statistical understanding to conceptual business scenarios. Business Insight Videos show students how statistical methods are used by real businesses, and new StatTalk Videos present statistical concepts through a series of fun, brief, real-world examples. Technology tutorial videos at the exercise level support software use.

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The Poisson-Dirichlet Distribution and Related Topics ab 82.49 EURO Models and Asymptotic Behaviors

Anbieter: ebook.de

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A gravity model is used to evaluate the manufacturing trade potential of the Central and Eastern European Countries (CEEC) with the EU15 countries from 1999 to 2002. Special attention is paid to this enlargement s effect on the Cohesion Countries (CC) within this approach. Relatively to previous studies, this monograph is, to the best of our knowledge, the first combining a trade potential based on the gravity model with the inclusion of a variable related to the Commodity Composition of Trade (CCT) in terms of manufactures. Several CCT variables were tested for the available data, taking into consideration high levels of disaggregation. Finally, having in consideration the latest academic debate in course, we analysed and tested all the methodological contributions recently proposed in the literature as regards to the improvement of the econometric specification of the gravity model, namely making use of the Poisson Pseudo-Maximum Likelihood Estimator. The refinement of the explanatory variables considered in the analysis, specifically those related to the distance measurement, as well as the introduction of new variables, were also taken into consideration.

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Spike-triggered covariance (STC) analysis is a tool for characterizing a neuron's response properties using the covariance of stimuli that elicit spikes from a neuron. STC is related to the spike-triggered average (STA), and provides a complementary tool for estimating linear filters in a linear-nonlinear-Poisson (LNP) cascade model. Unlike STA, the STC can be used to identify a multi-dimensional feature space in which a neuron computes its response. STC analysis identifies the stimulus features affecting a neuron's response via an eigenvector decomposition of the spike-triggered covariance matrix. Eigenvectors with eigenvalues significantly larger or smaller than the eigenvalues of the raw stimulus covariance correspond to stimulus axes along which the neural response is enhanced or suppressed.

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The economic development of a country and the health status of its society are intertwined. For a developing country like Ethiopia, that has been striving to eradicate poverty and bring about improvement in the society's welfare, understanding factors that affect the health status of the society is imperative. There are very few empirical studies that address this topic in the case of Ethiopia. This book therefore, provides information on the socioeconomic determinants of demand for health and health care in Ethiopia based on the theoretical foundations of the Grossman's health demand model using a relatively large data set from the Welfare Monitoring Survey (2005). Self-reported incidence of illness and number of physician visits are used to measure demand for health and health care, respectively. Self-reported incidence of illness is modeled with Probit model while the number of physician visits is modeled with Zero- inflated Poisson model. The analysis should be useful for any scholar interested in health and development related issues and it should come in handy for policy makers who can devise strategies that could improve the society's heath performance.

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The book consists of three chapters. In chapter I, we introduce some notions and definitions for basic concepts of the theory of integrable bi-Hamiltonian systems. Several open problems related to our main results are also mentioned in this part. In chapter II. We applied the so-called Jordan-Kronecker decomposition theorem to study algebraic properties of the pencil generated by two constant compatible Poisson structures on a vector space. In particular, we study the linear automorphism group that preserves the pencil. In classical symplectic geometry, many fundamental results are based on the symplectic group, which preserves the symplectic structure. Therefore in the theory of bi-Hamiltonian structures, we hope the linear automorphism group also plays a fundamental role. In chapter III, We describe the Lie group of linear automorphisms of the pencil, and obtain an explicit formula for the dimension of the Lie group and discuss some other algebraic properties such as solvability and Levi-Malcev decomposition.

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Though a lot of research work is done with Pareto distribution as a basic model, inspired by the contents and some remarks in chapter 20 of Johnson etal (2004). The Pareto distribution called P (IV) model is selected for the purpose of our research investigation. Pareto distribution in its various forms is a model, finding applications in economics related random phenomena. A little attention is paid earlier in reliability and quality control applications. We found that the following aspects need further investigation on P(IV) model: i) Estimation of parameters from complete and censored samples using maximum likelihood, Modified maximum likelihood and Quantile Methods. ii) Estimation of parameters in Length Biased, Modified versions. iii) Development of it as a software reliability growth model through the use of Non Homogeneous Poisson Process. iv) Construction of acceptance sampling plans and the associated performance measures based on life tests with test data modeled by P (IV) type distribution. The research findings out of the study on the above aspects are included in this book, is useful for budding scholars and quality control practitioners.

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