elements distribution theory de severini thomas (43 résultats)

Etat : Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.

Etat : Very Good. Item in very good condition! Textbooks may not include supplemental items i.e. CDs, access codes etc.

paperback. Etat : New. 1st Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

Etat : New.

Etat : New.

Hardcover. Etat : As New. newish copy xc for bookplate, inside front cover; then all NEW; 515pp all new all clean; we ship daily at 0900 CT IL USA; I ship anywhere you wish;

Paperback. Etat : new. Paperback. This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important and a course in elementary mathematical analysis is useful, but not required. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Topics covered range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals, orthogonal polynomials and saddlepoint approximations. The emphasis is on topics useful in understanding statistical methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are covered comprehensively. This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics and researchers who use statistical methods. Backgrounds in calculus and linear algebra are important, and a course in elementary mathematical analysis useful, but not required. An appendix summarizes the mathematical definitions and results outlined. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Etat : New. In.

Etat : New.

Etat : Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1150grams, ISBN:9780521844727.

Etat : Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In fair condition, suitable as a study copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1150grams, ISBN:9780521844727.

Etat : New. pp. 528.

Hardcover. Etat : new. Excellent Condition.Excels in customer satisfaction, prompt replies, and quality checks.

Etat : New.

Etat : New.

Paperback. Etat : new. Paperback. This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important and a course in elementary mathematical analysis is useful, but not required. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Topics covered range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals, orthogonal polynomials and saddlepoint approximations. The emphasis is on topics useful in understanding statistical methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are covered comprehensively. This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics and researchers who use statistical methods. Backgrounds in calculus and linear algebra are important, and a course in elementary mathematical analysis useful, but not required. An appendix summarizes the mathematical definitions and results outlined. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Etat : New.

Paperback. Etat : new. Paperback. This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important and a course in elementary mathematical analysis is useful, but not required. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Topics covered range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals, orthogonal polynomials and saddlepoint approximations. The emphasis is on topics useful in understanding statistical methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are covered comprehensively. This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics and researchers who use statistical methods. Backgrounds in calculus and linear algebra are important, and a course in elementary mathematical analysis useful, but not required. An appendix summarizes the mathematical definitions and results outlined. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Etat : New. In.

Hardcover. Etat : new. Hardcover. This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important and a course in elementary mathematical analysis is useful, but not required. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Topics covered range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals, orthogonal polynomials, and saddlepoint approximations. The emphasis is on topics useful in understanding statistical methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are covered comprehensively. This detailed introduction to distribution theory is designed as a text for the probability portion of the first year statistical theory sequence for Master's and PhD students in statistics, biostatistics, and econometrics. The text uses no measure theory, requiring only a background in calculus and linear algebra. Topics range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals and orthogonal polynomials. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Etat : New.

Etat : Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1150grams, ISBN:9780521844727.

Etat : As New. Unread book in perfect condition.

Hardcover. Etat : Like New. Like New. book.

Etat : As New. Unread book in perfect condition.

Etat : As New. Unread book in perfect condition.

Paperback. Etat : Like New. Like New. book.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important and a course in elementary mathematical analysis is useful, but not required. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Topics covered range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals, orthogonal polynomials and saddlepoint approximations. The emphasis is on topics useful in understanding statistical methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are covered comprehensively. This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics and researchers who use statistical methods. Backgrounds in calculus and linear algebra are important, and a course in elementary mathematical analysis useful, but not required. An appendix summarizes the mathematical definitions and results outlined.

Etat : As New. Unread book in perfect condition.

Hardcover. Etat : new. Hardcover. This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important and a course in elementary mathematical analysis is useful, but not required. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Topics covered range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals, orthogonal polynomials, and saddlepoint approximations. The emphasis is on topics useful in understanding statistical methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are covered comprehensively. This detailed introduction to distribution theory is designed as a text for the probability portion of the first year statistical theory sequence for Master's and PhD students in statistics, biostatistics, and econometrics. The text uses no measure theory, requiring only a background in calculus and linear algebra. Topics range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals and orthogonal polynomials. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.