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Stadistical Inference
Casella, George
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Últimas novedades
estadística
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This book builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. Intended for first-year graduate students, this book can be used for students majoring in statistics who have a solid mathematics background. It can also be used in a way that stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures for a variety of situations, and less concerned with formal optimality investigations.
Features
Begins with the basics of probability theory and introduces many fundamentals that are later necessary (Chapters
Treats likelihood and sufficiency principles in detail. These principles, and the thinking behind them, are fundamental to total statistical understanding. The equivariance principle is also introduced.
Divides the methods of finding appropriate statistical methods and the methods of evaluating these techniques in the core statistical inference chapters (Chapters 7-9). Integrates decision theoretic evaluations into core chapters. Many of the techniques are used in consulting and are helpful in analyzing and inferring from actual problems.
Discusses use of simulation in mathematical statistics.
Includes a thorough introduction to large sample statistical methods.
Covers the elementary linear models through simple linear regression and oneway analysis of variance.
Covers more advanced theory of regression topics including "errors in variables" regression, logistic regression, and robust regression.
1. Probability Theory.
Set Theory. Probability Theory. Conditional Probability and Independence. Random Variables. Distribution
Functions. Density and Mass Functions. Exercises. Miscellanea.
2. Transformations and Expectations.
Distribution of Functions of a Random Variable. Expected Values. Moments and Moment Generating
Functions. Differentiating Under an Integral Sign. Exercises. Miscellanea.
3. Common Families of Distributions.
Introductions. Discrete Distributions. Continuous Distributions. Exponential Families. Locations and Scale
Families. Inequalities and Identities. Exercises. Miscellanea.
4. Multiple Random Variables.
Joint and Marginal Distributions. Conditional Distributions and Independence. Bivariate Transformations. Hierarchical Models and Mixture Distributions. Covariance and Correlation. Multivariate Distributions. Inequalities. Exercises. Miscellanea.
5. Properties of a Random Sample.
Basic Concepts of Random Samples. Sums of Random Variables from a Random Sample. Sampling for the Normal Distribution. Order Statistics. Convergence Concepts. Generating a Random Sample. Exercises. Miscellanea.
6. Principles of Data Reduction.
Introduction. The Sufficiency Principle. The Likelihood Principle. The Equivariance Principle. Exercises. Miscellanea.
7. Point Estimation.
Introduction. Methods of Finding Estimators. Methods of Evaluating Estimators. Exercises. Miscellanea.
8. Hypothesis Testing.
Introduction. Methods of Finding Tests. Methods of Evaluating Test. Exercises. Miscellanea.
9. Interval Estimation.
Introduction. Methods of Finding Interval Estimators. Methods of Evaluating Interval Estimators. Exercises. Miscellanea.
10. Asymptotic Evaluations.
Point Estimation. Robustness. Hypothesis Testing. Interval Estimation. Exercises. Miscellanea.
11. Analysis of Variance and Regression.
Introduction. One-way Analysis of Variance. Simple Linear Regression. Exercises. Miscellanea.
12. Regression Models.
Introduction. Regression with Errors in Variables. Logistic Regression. Robust Regression. Exercises. Miscellanea. Appendix. Computer Algebra. References.
Offers new coverage of random number generation, simulation methods, bootstrapping, EM algorithm, p-values, and robustness.Restructures material for clarity purposes.Gathers all large sample results into Chapter 10.Includes a new section on "Generating a Random Sample" in Chapter 5.Includes new sections on "Logistic Regression" and "Robust Regression" in Chapter 12.Contains updated and expanded Exercises in all chapters, and updated and expanded Miscellanea including discussions of variations on likelihood and Bayesian analysis, bootstrap, "second-order" asymptotics, and Monte Carlo Markov chain.Contains an Appendix detailing the use of Mathematica in problem solving.
{Supplements}
{Quotes}
George Casella
Roger L. Berger
HomeInstructors
New TitlesGeneral Chemistry TextbookPhysics for the Life Sciences TextbookOrder Inspection CopiesOnline ResourcesRep locatorStudents
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AccountingBusiness & TechnologyBusiness CommunicationBusiness EducationBusiness LawBusiness MathematicsBusiness StatisticsCareer Investigation & ReadinessCertificationCommunicationsComputer ApplicationsComputer EducationDecision SciencesEconomicsFinanceIntroduction to BusinessManagementMarketingOffice TechnologyReal EstateReferenceTaxationTechnologyAnthropologyArtCommunication and MediaCounselling/PsychotherapyCriminal JusticeDevelopmental EnglishEnglishEnglish as a Second LanguageFrenchGermanHistoryHuman ServicesItalianModern LanguageMusicPhilosophyPolitical SciencePsychologyReligionSocial WorkSociologySpanishAstronomyChemistryEarth ScienceEngineeringHealthLife SciencesMathematicsNutritionOceanographyPhysicsAssessment, Training, and ProjectsComputer ConceptsComputer ScienceDatabasesGame Design & DevelopmentGraphic CommunicationsHelp Desk/Desktop SupportInternetMedia Arts & DesignMISMusic TechnologyNetworking & SecurityOffice SuitesOperating SystemsPC Repair/A+Presentation ToolsProgrammingProject ManagementSoft SkillsSpreadsheetsWeb Design & DevelopmentWord ProcessingAgriscienceAutomotive and MechanicsAviationCatering and HospitalityCollege SuccessEducationElectronics and EngineeringHair & BeautyLeisure and ToursimNursing, Medical and DentistryPhotography, Multimedia and DesignProfessional Development and Study SkillsTradesCengage Learning EMEAEnglish Language TeachingGlobalHigher EducationLibrary & ReferenceAbout UsCopyright, Terms & ConditionsPrivacy PolicyContact UsCareersWebsite Design by Mulberry Interactive Ltd |
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1. Probability Theory.
Set Theory. Probability Theory. Conditional Probability and Independence. Random Variables. Distribution
Functions. Density and Mass Functions. Exercises. Miscellanea.
2. Transformations and Expectations.
Distribution of Functions of a Random Variable. Expected Values. Moments and Moment Generating
Functions. Differentiating Under an Integral Sign. Exercises. Miscellanea.
3. Common Families of Distributions.
Introductions. Discrete Distributions. Continuous Distributions. Exponential Families. Locations and Scale
Families. Inequalities and Identities. Exercises. Miscellanea.
4. Multiple Random Variables.
Joint and Marginal Distributions. Conditional Distributions and Independence. Bivariate Transformations. Hierarchical Models and Mixture Distributions. Covariance and Correlation. Multivariate Distributions. Inequalities. Exercises. Miscellanea.
5. Properties of a Random Sample.
Basic Concepts of Random Samples. Sums of Random Variables from a Random Sample. Sampling for the Normal Distribution. Order Statistics. Convergence Concepts. Generating a Random Sample. Exercises. Miscellanea.
6. Principles of Data Reduction.
Introduction. The Sufficiency Principle. The Likelihood Principle. The Equivariance Principle. Exercises. Miscellanea.
7. Point Estimation.
Introduction. Methods of Finding Estimators. Methods of Evaluating Estimators. Exercises. Miscellanea.
8. Hypothesis Testing.
Introduction. Methods of Finding Tests. Methods of Evaluating Test. Exercises. Miscellanea.
9. Interval Estimation.
Introduction. Methods of Finding Interval Estimators. Methods of Evaluating Interval Estimators. Exercises. Miscellanea.
10. Asymptotic Evaluations.
Point Estimation. Robustness. Hypothesis Testing. Interval Estimation. Exercises. Miscellanea.
11. Analysis of Variance and Regression.
Introduction. One-way Analysis of Variance. Simple Linear Regression. Exercises. Miscellanea.
12. Regression Models.
Introduction. Regression with Errors in Variables. Logistic Regression. Robust Regression. Exercises. Miscellanea. Appendix. Computer Algebra. References.
Offers new coverage of random number generation, simulation methods, bootstrapping, EM algorithm, p-values, and robustness.Restructures material for clarity purposes.Gathers all large sample results into Chapter 10.Includes a new section on "Generating a Random Sample" in Chapter 5.Includes new sections on "Logistic Regression" and "Robust Regression" in Chapter 12.Contains updated and expanded Exercises in all chapters, and updated and expanded Miscellanea including discussions of variations on likelihood and Bayesian analysis, bootstrap, "second-order" asymptotics, and Monte Carlo Markov chain.Contains an Appendix detailing the use of Mathematica in problem solving.
{Supplements}
{Quotes}
George Casella
Roger L. Berger
HomeInstructors
New TitlesGeneral Chemistry TextbookPhysics for the Life Sciences TextbookOrder Inspection CopiesOnline ResourcesRep locatorStudents
Online Student ResourcesBookshopsAuthors
Review processProposal guidelinesUnited KingdomChange your regionSearch Go
AccountingBusiness & TechnologyBusiness CommunicationBusiness EducationBusiness LawBusiness MathematicsBusiness StatisticsCareer Investigation & ReadinessCertificationCommunicationsComputer ApplicationsComputer EducationDecision SciencesEconomicsFinanceIntroduction to BusinessManagementMarketingOffice TechnologyReal EstateReferenceTaxationTechnologyAnthropologyArtCommunication and MediaCounselling/PsychotherapyCriminal JusticeDevelopmental EnglishEnglishEnglish as a Second LanguageFrenchGermanHistoryHuman ServicesItalianModern LanguageMusicPhilosophyPolitical SciencePsychologyReligionSocial WorkSociologySpanishAstronomyChemistryEarth ScienceEngineeringHealthLife SciencesMathematicsNutritionOceanographyPhysicsAssessment, Training, and ProjectsComputer ConceptsComputer ScienceDatabasesGame Design & DevelopmentGraphic CommunicationsHelp Desk/Desktop SupportInternetMedia Arts & DesignMISMusic TechnologyNetworking & SecurityOffice SuitesOperating SystemsPC Repair/A+Presentation ToolsProgrammingProject ManagementSoft SkillsSpreadsheetsWeb Design & DevelopmentWord ProcessingAgriscienceAutomotive and MechanicsAviationCatering and HospitalityCollege SuccessEducationElectronics and EngineeringHair & BeautyLeisure and ToursimNursing, Medical and DentistryPhotography, Multimedia and DesignProfessional Development and Study SkillsTradesCengage Learning EMEAEnglish Language TeachingGlobalHigher EducationLibrary & ReferenceAbout UsCopyright, Terms & ConditionsPrivacy PolicyContact UsCareersWebsite Design by Mulberry Interactive Ltd |
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