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Showing 1 - 4 of 4 matches in All Departments
After a one-woman assault on the Umbrella Corporation's fortress, Alice's superhuman abilities are neutralized. Now, fleeing the Undead masses created by the T-virus, Alice reunites with Claire Redfield and her brother, Chris. Together they take refuge with other survivors in an abandoned prison, where a savage zombie mob stands between them and the safety of "Arcadia." Escaping these bloodthirsty mutants will take an arsenal. But facing off with Albert Wesker and the Umbrella Corporation will take the fight for survival to a new level of danger.
Sword-and-sandal disaster epic directed by Paul W.S. Anderson and starring Kit Harington. Set before and during the Mount Vesuvius eruption of 79 AD, the film follows the plight of slave-turned-gladiator Milo (Harington) who falls in love with Cassia (Emily Browning), the daughter of a wealthy merchant who has recently become engaged to Corvus (Kiefer Sutherland), an influential Roman Senator. As the mountain erupts and quickly destroys the city of Pompeii as well as its surrounding communities, Milo must track down his one true love before all hope of survival is annihilated.
This book describes the basis, application, and interpretation of statistics, and presents a wide range of univariate and multivariate statistical methodology. In its first edition it has proved popular across all science and technology based disciplines, including the social sciences, and in areas of commerce. It is used both as a reference on statistical methodology for researchers and technicians, and as a textbook with particular appeal for graduate classes containing students of mixed mathematical and statistical background. The book is developed without the use of calculus, although several self-contained sections containing calculus are included to provide additional insight for readers who have a calculus background. Based on the author's "Statistics in Scientific Investigation," the book has been extended substantially in the area of multivariate applications and through the expansion of logistic regression and log linear methodology. It presumes readers have access to a statistical computing package and includes guidance on the application of statistical computing packages. The new edition retains the unique feature of being written from the users' perspective; it connects statistical models and methods to investigative questions and background information, and connects statistical results with interpretations in plain English. In keeping with this approach, methods are grouped by usage rather than by commonality of statistical methodology. Guidance is provided on the choice of appropriate methods. The use of real life examples has been retained and expanded. Using the power of the Internet, expanded reports on the examples are available at a Springer Web site as Word documents. Additionaly, all data sets are available at the Web site as Excel files, and program files and data sets are provided for SAS users and SPSS users. The programs are annotated so users can adapt for their own data sets. Glen McPherson has had a long career as an acedmic and a consultant in applied statistics. After holding a tenured position for thirty years at The University of Tasmania in Australia, where he developed and directed under-graduate and gradate programs in applied statistics, he resigned to devote more time to book writing and to his consultancy role to government , business, and industry. The practical experience built into the book is drawn from the two thousand consulantcies he has undetaken across virtually all areas in which statistics has an application.
This book describes the basis, application, and interpretation of statistics, and presents a wide range of univariate and multivariate statistical methodology. In its first edition it has proved popular across all science and technology based disciplines, including the social sciences, and in areas of commerce. It is used both as a reference on statistical methodology for researchers and technicians, and as a textbook with particular appeal for graduate classes containing students of mixed mathematical and statistical background. The book is developed without the use of calculus, although several self-contained sections containing calculus are included to provide additional insight for readers who have a calculus background. Based on the author's "Statistics in Scientific Investigation," the book has been extended substantially in the area of multivariate applications and through the expansion of logistic regression and log linear methodology. It presumes readers have access to a statistical computing package and includes guidance on the application of statistical computing packages. The new edition retains the unique feature of being written from the users' perspective; it connects statistical models and methods to investigative questions and background information, and connects statistical results with interpretations in plain English. In keeping with this approach, methods are grouped by usage rather than by commonality of statistical methodology. Guidance is provided on the choice of appropriate methods. The use of real life examples has been retained and expanded. Using the power of the Internet, expanded reports on the examples are available at a Springer Web site as Word documents. Additionaly, all data sets are available at the Web site as Excel files, and program files and data sets are provided for SAS users and SPSS users. The programs are annotated so users can adapt for their own data sets. Glen McPherson has had a long career as an acedmic and a consultant in applied statistics. After holding a tenured position for thirty years at The University of Tasmania in Australia, where he developed and directed under-graduate and gradate programs in applied statistics, he resigned to devote more time to book writing and to his consultancy role to government, business, and industry. The practical experience built into the book is drawn from the two thousand consulantcies he has undetaken across virtually all areas in which statistics has an application.
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