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Hardcover. Condizione: Très bon. Ancien livre de bibliothèque. Salissures sur la tranche. Edition 2008. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Stains on the edge. Edition 2008. Ammareal gives back up to 15% of this item's net price to charity organizations. …

Condizione: new.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New.

Condizione: New. pp. 400.

Condizione: New.

Condizione: New. pp. 400.

Hardback. Condizione: New. The first all-inclusive introduction to modern statistical research methods in the natural resource sciences The use of Bayesian statistical analysis has become increasingly important to natural resource scientists as a practical tool for solving various research problems. However, many important contemporary methods of applied statistics, such as generalized linear modeling, mixed-effects modeling, and Bayesian statistical analysis and inference, remain relatively unknown among researchers and practitioners in this field. Through its inclusive, hands-on treatment of real-world examples, Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists successfully introduces the key concepts of statistical analysis and inference with an accessible, easy-to-follow approach. The book provides case studies illustrating common problems that exist in the natural resource sciences and presents the statistical knowledge and tools needed for a modern treatment of these issues. Subsequent chapter coverage features: An introduction to the fundamental concepts of Bayesian statistical analysis, including its historical background, conjugate solutions, Bayesian hypothesis testing and decision-making, and Markov Chain Monte Carlo solutions The relevant advantages of using Bayesian statistical analysis, rather than the traditional frequentist approach, to address research problems Two alternative strategiesâ?"the a posteriori model selection strategy and the a priori parsimonious model selection strategy using AIC and DICâ?"to model selection and inference The ideas of generalized linear modeling (GLM), focusing on the most popular GLM of logistic regression An introduction to mixed-effects modeling in S-Plus® and R for analyzing natural resource data sets with varying error structures and dependencies Each statistical concept is accompanied by an illustration of its frequentist application in S-Plus® or R as well as its Bayesian application in WinBUGS. Brief introductions to these software packages are also provided to help the reader fully understand the concepts of the statistical methods that are presented throughout the book. Assuming only a minimal background in introductory statistics, Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists is an ideal text for natural resource students studying statistical research methods at the upper-undergraduate or graduate level and also serves as a valuable problem-solving guide for natural resource scientists across a broad range of disciplines, including biology, wildlife management, forestry management, fisheries management, and the environmental sciences. …

Condizione: New. In English.

Hardcover. Condizione: new. Hardcover. The first all-inclusive introduction to modern statistical research methods in the natural resource sciences The use of Bayesian statistical analysis has become increasingly important to natural resource scientists as a practical tool for solving various research problems. However, many important contemporary methods of applied statistics, such as generalized linear modeling, mixed-effects modeling, and Bayesian statistical analysis and inference, remain relatively unknown among researchers and practitioners in this field. Through its inclusive, hands-on treatment of real-world examples, Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists successfully introduces the key concepts of statistical analysis and inference with an accessible, easy-to-follow approach. The book provides case studies illustrating common problems that exist in the natural resource sciences and presents the statistical knowledge and tools needed for a modern treatment of these issues. Subsequent chapter coverage features: An introduction to the fundamental concepts of Bayesian statistical analysis, including its historical background, conjugate solutions, Bayesian hypothesis testing and decision-making, and Markov Chain Monte Carlo solutions The relevant advantages of using Bayesian statistical analysis, rather than the traditional frequentist approach, to address research problems Two alternative strategiesathe a posteriori model selection strategy and the a priori parsimonious model selection strategy using AIC and DICato model selection and inference The ideas of generalized linear modeling (GLM), focusing on the most popular GLM of logistic regression An introduction to mixed-effects modeling in S-PlusA and R for analyzing natural resource data sets with varying error structures and dependencies Each statistical concept is accompanied by an illustration of its frequentist application in S-PlusA or R as well as its Bayesian application in WinBUGS. Brief introductions to these software packages are also provided to help the reader fully understand the concepts of the statistical methods that are presented throughout the book. Assuming only a minimal background in introductory statistics, Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists is an ideal text for natural resource students studying statistical research methods at the upper-undergraduate or graduate level and also serves as a valuable problem-solving guide for natural resource scientists across a broad range of disciplines, including biology, wildlife management, forestry management, fisheries management, and the environmental sciences. The first all-inclusive introduction to modern statistical research methods in the natural resource sciences he use of Bayesian statistical analysis has become increasingly important to natural resource scientists as a practical tool for solving various research problems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardback. Condizione: New. New copy - Usually dispatched within 4 working days.

Condizione: New. The first all-inclusive introduction to modern statistical research methods in the natural resource sciences he use of Bayesian statistical analysis has become increasingly important to natural resource scientists as a practical tool for solving various research problems. Num Pages: 400 pages, Illustrations. BIC Classification: GPS; PBT. Category: (P) Professional & Vocational. Dimension: 232 x 163 x 25. Weight in Grams: 710. . 2007. 1st Edition. Hardcover. . . . . …

Hardcover. Condizione: Brand New. illustrated edition. 400 pages. 9.50x6.50x1.00 inches. In Stock.

Condizione: As New. Unread book in perfect condition.

Hardcover. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condizione: As New. Unread book in perfect condition.

Condizione: New. The first all-inclusive introduction to modern statistical research methods in the natural resource sciences he use of Bayesian statistical analysis has become increasingly important to natural resource scientists as a practical tool for solving various research problems. Num Pages: 400 pages, Illustrations. BIC Classification: GPS; PBT. Category: (P) Professional & Vocational. Dimension: 232 x 163 x 25. Weight in Grams: 710. . 2007. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland. …

Hardback. Condizione: New. The first all-inclusive introduction to modern statistical research methods in the natural resource sciences The use of Bayesian statistical analysis has become increasingly important to natural resource scientists as a practical tool for solving various research problems. However, many important contemporary methods of applied statistics, such as generalized linear modeling, mixed-effects modeling, and Bayesian statistical analysis and inference, remain relatively unknown among researchers and practitioners in this field. Through its inclusive, hands-on treatment of real-world examples, Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists successfully introduces the key concepts of statistical analysis and inference with an accessible, easy-to-follow approach. The book provides case studies illustrating common problems that exist in the natural resource sciences and presents the statistical knowledge and tools needed for a modern treatment of these issues. Subsequent chapter coverage features: An introduction to the fundamental concepts of Bayesian statistical analysis, including its historical background, conjugate solutions, Bayesian hypothesis testing and decision-making, and Markov Chain Monte Carlo solutions The relevant advantages of using Bayesian statistical analysis, rather than the traditional frequentist approach, to address research problems Two alternative strategiesâ?"the a posteriori model selection strategy and the a priori parsimonious model selection strategy using AIC and DICâ?"to model selection and inference The ideas of generalized linear modeling (GLM), focusing on the most popular GLM of logistic regression An introduction to mixed-effects modeling in S-Plus® and R for analyzing natural resource data sets with varying error structures and dependencies Each statistical concept is accompanied by an illustration of its frequentist application in S-Plus® or R as well as its Bayesian application in WinBUGS. Brief introductions to these software packages are also provided to help the reader fully understand the concepts of the statistical methods that are presented throughout the book. Assuming only a minimal background in introductory statistics, Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists is an ideal text for natural resource students studying statistical research methods at the upper-undergraduate or graduate level and also serves as a valuable problem-solving guide for natural resource scientists across a broad range of disciplines, including biology, wildlife management, forestry management, fisheries management, and the environmental sciences. …

Hardcover. Condizione: new. Hardcover. The first all-inclusive introduction to modern statistical research methods in the natural resource sciences The use of Bayesian statistical analysis has become increasingly important to natural resource scientists as a practical tool for solving various research problems. However, many important contemporary methods of applied statistics, such as generalized linear modeling, mixed-effects modeling, and Bayesian statistical analysis and inference, remain relatively unknown among researchers and practitioners in this field. Through its inclusive, hands-on treatment of real-world examples, Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists successfully introduces the key concepts of statistical analysis and inference with an accessible, easy-to-follow approach. The book provides case studies illustrating common problems that exist in the natural resource sciences and presents the statistical knowledge and tools needed for a modern treatment of these issues. Subsequent chapter coverage features: An introduction to the fundamental concepts of Bayesian statistical analysis, including its historical background, conjugate solutions, Bayesian hypothesis testing and decision-making, and Markov Chain Monte Carlo solutions The relevant advantages of using Bayesian statistical analysis, rather than the traditional frequentist approach, to address research problems Two alternative strategiesathe a posteriori model selection strategy and the a priori parsimonious model selection strategy using AIC and DICato model selection and inference The ideas of generalized linear modeling (GLM), focusing on the most popular GLM of logistic regression An introduction to mixed-effects modeling in S-PlusA and R for analyzing natural resource data sets with varying error structures and dependencies Each statistical concept is accompanied by an illustration of its frequentist application in S-PlusA or R as well as its Bayesian application in WinBUGS. Brief introductions to these software packages are also provided to help the reader fully understand the concepts of the statistical methods that are presented throughout the book. Assuming only a minimal background in introductory statistics, Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists is an ideal text for natural resource students studying statistical research methods at the upper-undergraduate or graduate level and also serves as a valuable problem-solving guide for natural resource scientists across a broad range of disciplines, including biology, wildlife management, forestry management, fisheries management, and the environmental sciences. The first all-inclusive introduction to modern statistical research methods in the natural resource sciences he use of Bayesian statistical analysis has become increasingly important to natural resource scientists as a practical tool for solving various research problems. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Hardcover. Condizione: Very Good. First Edition. 46 volume set. A large library of the Green books, US Army in World War II series. Green GPO buckram cloth. 26 cm. Hardcover. Good bindings and covers. Some volumes have name stamps (mostly former US Army officer staff from the Army War College). This is a massive, oversized set, which WILL require additional postage for Priority or international delivery outside the US. Includes: The War against Germany and Italy: Mediterranean and Adjacent Areas (PICTORIAL RECORD);The War Against Germany: Europe and Adjacent Areas (PICTORIAL RECORD); The War against Japan (PICTORIAL RECORD);Sicily and the Surrender of Italy; Northwest Africa: Seizing the Initiative in the West;Cassino to the Alps; The Army and Economic Mobilization; Strategic Planning for Coalition Warfare, 1941-1942; Time Runs Out in CBI; Strategy and Command: The First Two Years; Campaign in the Marianas; Seizure of the Gilberts and Marshalls; Victory in Papua; Guadalcanal: The First Offensive; The Approach to the Philippines; Triumph in the Philippines; Okinawa: The Last Battle; The Lorraine Campaign;Riviera to the Rhine;Logistical Support of the Armies, Volume I: May 1941-September 1944; Logistical Support of the Armies, Volume II: September 1944-May 1945; The Siegfried Line Campaign; The Ardennes: Battle of the Bulge; The Women's Army Corps; Buying Aircraft: Materiel Procurement for the Army Air Forces ; Manhattan: The Army and the Atomic Bomb; The Organization and Role of the Army Service Forces; Guarding the United States and Its Outposts; The Corps of Engineers: The War Against Japan; The Corps of Engineers: Troops and Equipment; The Corps of Engineers: The War Against Germany; The Transportation Corps: Movements, Training, and Supply; The Transportation Corps: Responsibilities, Organization, and Operations; The Ordnance Department: On Beachhead and Battlefront; The Ordnance Department: Procurement and Supply; The Ordnance Department: Planning Munitions for War; The Signal Corps: The Emergency (To December 1941); The Signal Corps: The Outcome (Mid-1943 Through 1945); The Quartermaster Corps: Organization, Supply, and Services, Volume I; The Quartermaster Corps: Operations in the War Against Germany; The Quartermaster Corps: Operations in the War Against Japan; The Medical Department: Medical Service in the European Theater of Operations; The Medical Department: Hospitalization and Evacuation, Zone of the Interior; The Medical Department: Medical Service in the Mediterranean and Minor Theaters; The Medical Department: Medical Service in the War Against Japan; The Employment of Negro Troops.…

Hardback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 740.

Hardcover. Condizione: new. Hardcover. The first all-inclusive introduction to modern statistical research methods in the natural resource sciences The use of Bayesian statistical analysis has become increasingly important to natural resource scientists as a practical tool for solving various research problems. However, many important contemporary methods of applied statistics, such as generalized linear modeling, mixed-effects modeling, and Bayesian statistical analysis and inference, remain relatively unknown among researchers and practitioners in this field. Through its inclusive, hands-on treatment of real-world examples, Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists successfully introduces the key concepts of statistical analysis and inference with an accessible, easy-to-follow approach. The book provides case studies illustrating common problems that exist in the natural resource sciences and presents the statistical knowledge and tools needed for a modern treatment of these issues. Subsequent chapter coverage features: An introduction to the fundamental concepts of Bayesian statistical analysis, including its historical background, conjugate solutions, Bayesian hypothesis testing and decision-making, and Markov Chain Monte Carlo solutions The relevant advantages of using Bayesian statistical analysis, rather than the traditional frequentist approach, to address research problems Two alternative strategiesathe a posteriori model selection strategy and the a priori parsimonious model selection strategy using AIC and DICato model selection and inference The ideas of generalized linear modeling (GLM), focusing on the most popular GLM of logistic regression An introduction to mixed-effects modeling in S-PlusA and R for analyzing natural resource data sets with varying error structures and dependencies Each statistical concept is accompanied by an illustration of its frequentist application in S-PlusA or R as well as its Bayesian application in WinBUGS. Brief introductions to these software packages are also provided to help the reader fully understand the concepts of the statistical methods that are presented throughout the book. Assuming only a minimal background in introductory statistics, Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists is an ideal text for natural resource students studying statistical research methods at the upper-undergraduate or graduate level and also serves as a valuable problem-solving guide for natural resource scientists across a broad range of disciplines, including biology, wildlife management, forestry management, fisheries management, and the environmental sciences. The first all-inclusive introduction to modern statistical research methods in the natural resource sciences he use of Bayesian statistical analysis has become increasingly important to natural resource scientists as a practical tool for solving various research problems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Hardcover. Condizione: Brand New. illustrated edition. 400 pages. 9.50x6.50x1.00 inches. In Stock. This item is printed on demand.