Introduction Computer Intensive Methods Data by Roff Derek (26 results)

Hardcover. Condition: Like New. First Edition. Bright and clean, firm and square, just a few very minor rubs. Hence a non-text page is stamped 'damaged'. Despite such this book is actually in nearly new condition. Thus it looks and feels unread with contents that are crisp, fresh and tight. Now offered for sale at a special bargain price.

Condition: New.

Condition: New.

Paperback. Condition: New.

Condition: New. In.

Paperback. Condition: new. Paperback. This 2006 guide to the contemporary toolbox of methods for data analysis will serve graduate students and researchers across the biological sciences. Modern computational tools, such as Maximum Likelihood, Monte Carlo and Bayesian methods, mean that data analysis no longer depends on elaborate assumptions designed to make analytical approaches tractable. These new 'computer-intensive' methods are currently not consistently available in statistical software packages and often require more detailed instructions. The purpose of this book therefore is to introduce some of the most common of these methods by providing a relatively simple description of the techniques. Examples of their application are provided throughout, using real data taken from a wide range of biological research. A series of software instructions for the statistical software package S-PLUS are provided along with problems and solutions for each chapter. This 2006 graduate text introduces some of the most common computer-intensive methods, including Maximum Likelihood, Monte Carlo and Bayesian methods. Examples of their application using biological data are provided, along with a series of software instructions for the statistical software package S-PLUS and problems and solutions are included to aid understanding. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condition: Good.

Softcover. Condition: Very Good. 368pp. Pictorial laminated light card covers. 8vo. Light chipping to edges and wear to covers, corners starting to curl; crease to top front corner. Previous owner's label on title page. Internally, neat, clean, bright and tight.

Paperback. Condition: new. Paperback. This 2006 guide to the contemporary toolbox of methods for data analysis will serve graduate students and researchers across the biological sciences. Modern computational tools, such as Maximum Likelihood, Monte Carlo and Bayesian methods, mean that data analysis no longer depends on elaborate assumptions designed to make analytical approaches tractable. These new 'computer-intensive' methods are currently not consistently available in statistical software packages and often require more detailed instructions. The purpose of this book therefore is to introduce some of the most common of these methods by providing a relatively simple description of the techniques. Examples of their application are provided throughout, using real data taken from a wide range of biological research. A series of software instructions for the statistical software package S-PLUS are provided along with problems and solutions for each chapter. This 2006 graduate text introduces some of the most common computer-intensive methods, including Maximum Likelihood, Monte Carlo and Bayesian methods. Examples of their application using biological data are provided, along with a series of software instructions for the statistical software package S-PLUS and problems and solutions are included to aid understanding. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condition: Good. Good. book.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This 2006 guide to the contemporary toolbox of methods for data analysis will serve graduate students and researchers across the biological sciences. Modern computational tools, such as Maximum Likelihood, Monte Carlo and Bayesian methods, mean that data analysis no longer depends on elaborate assumptions designed to make analytical approaches tractable. These new 'computer-intensive' methods are currently not consistently available in statistical software packages and often require more detailed instructions. The purpose of this book therefore is to introduce some of the most common of these methods by providing a relatively simple description of the techniques. Examples of their application are provided throughout, using real data taken from a wide range of biological research. A series of software instructions for the statistical software package S-PLUS are provided along with problems and solutions for each chapter.

Paperback. Condition: new. Paperback. This 2006 guide to the contemporary toolbox of methods for data analysis will serve graduate students and researchers across the biological sciences. Modern computational tools, such as Maximum Likelihood, Monte Carlo and Bayesian methods, mean that data analysis no longer depends on elaborate assumptions designed to make analytical approaches tractable. These new 'computer-intensive' methods are currently not consistently available in statistical software packages and often require more detailed instructions. The purpose of this book therefore is to introduce some of the most common of these methods by providing a relatively simple description of the techniques. Examples of their application are provided throughout, using real data taken from a wide range of biological research. A series of software instructions for the statistical software package S-PLUS are provided along with problems and solutions for each chapter. This 2006 graduate text introduces some of the most common computer-intensive methods, including Maximum Likelihood, Monte Carlo and Bayesian methods. Examples of their application using biological data are provided, along with a series of software instructions for the statistical software package S-PLUS and problems and solutions are included to aid understanding. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Condition: New.

Condition: New. In.

Condition: New.

Hardcover. Condition: new. Hardcover. This 2006 guide to the contemporary toolbox of methods for data analysis will serve graduate students and researchers across the biological sciences. Modern computational tools, such as Maximum Likelihood, Monte Carlo and Bayesian methods, mean that data analysis no longer depends on elaborate assumptions designed to make analytical approaches tractable. These new 'computer-intensive' methods are currently not consistently available in statistical software packages and often require more detailed instructions. The purpose of this book therefore is to introduce some of the most common of these methods by providing a relatively simple description of the techniques. Examples of their application are provided throughout, using real data taken from a wide range of biological research. A series of software instructions for the statistical software package S-PLUS are provided along with problems and solutions for each chapter. This 2006 graduate text introduces some of the most common computer-intensive methods, including Maximum Likelihood, Monte Carlo and Bayesian methods. Examples of their application using biological data are provided, along with a series of software instructions for the statistical software package S-PLUS and problems and solutions are included to aid understanding. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Condition: new. Hardcover. This 2006 guide to the contemporary toolbox of methods for data analysis will serve graduate students and researchers across the biological sciences. Modern computational tools, such as Maximum Likelihood, Monte Carlo and Bayesian methods, mean that data analysis no longer depends on elaborate assumptions designed to make analytical approaches tractable. These new 'computer-intensive' methods are currently not consistently available in statistical software packages and often require more detailed instructions. The purpose of this book therefore is to introduce some of the most common of these methods by providing a relatively simple description of the techniques. Examples of their application are provided throughout, using real data taken from a wide range of biological research. A series of software instructions for the statistical software package S-PLUS are provided along with problems and solutions for each chapter. This 2006 graduate text introduces some of the most common computer-intensive methods, including Maximum Likelihood, Monte Carlo and Bayesian methods. Examples of their application using biological data are provided, along with a series of software instructions for the statistical software package S-PLUS and problems and solutions are included to aid understanding. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Hardcover. Condition: Like New. Like New. book.

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Modern computational tools, such as Maximum Likelihood, Monte Carlo and Bayesian methods, mean that data analysis no longer depends on elaborate assumptions designed to make analytical approaches tractable. This book introduces some of the most common of these methods by providing a relatively simple description of the techniques. Examples of their application are provided throughout, using real data taken from a wide range of biological research. A series of software instructions for the statistical software package S-PLUS are provided along with problems and solutions for each chapter.

Hardcover. Condition: new. Hardcover. This 2006 guide to the contemporary toolbox of methods for data analysis will serve graduate students and researchers across the biological sciences. Modern computational tools, such as Maximum Likelihood, Monte Carlo and Bayesian methods, mean that data analysis no longer depends on elaborate assumptions designed to make analytical approaches tractable. These new 'computer-intensive' methods are currently not consistently available in statistical software packages and often require more detailed instructions. The purpose of this book therefore is to introduce some of the most common of these methods by providing a relatively simple description of the techniques. Examples of their application are provided throughout, using real data taken from a wide range of biological research. A series of software instructions for the statistical software package S-PLUS are provided along with problems and solutions for each chapter. This 2006 graduate text introduces some of the most common computer-intensive methods, including Maximum Likelihood, Monte Carlo and Bayesian methods. Examples of their application using biological data are provided, along with a series of software instructions for the statistical software package S-PLUS and problems and solutions are included to aid understanding. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Paperback. Condition: Brand New. 1st edition. 368 pages. 9.25x6.75x0.50 inches. In Stock. This item is printed on demand.

Paperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 630.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This 2006 graduate text introduces some of the most common computer-intensive methods, including Maximum Likelihood, Monte Carlo and Bayesian methods. Examples of their application using biological data are provided, along with a series of software instruct.

Hardcover. Condition: Brand New. illustrated edition. 376 pages. 9.50x7.00x0.87 inches. In Stock. This item is printed on demand.

Hardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 923.

Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This 2006 graduate text introduces some of the most common computer-intensive methods, including Maximum Likelihood, Monte Carlo and Bayesian methods. Examples of their application using biological data are provided, along with a series of software instruct.