roshan joseph (26 risultati)

Condizione: New. pp. 232.

Condizione: New. pp. 232 First Edition NO-PA16APR2015-KAP.

Condizione: New. pp. 232.

Soft cover. Condizione: New. ISBN:9789352807123,204pp.

Soft cover. Condizione: New. ISBN:9789353289362,232pp.

Condizione: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.

Condizione: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.

Paperback. Condizione: New. Brand New ! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.

Paperback. Condizione: New. Brand New ! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.

Paperback. Condizione: Brand New. 204 pages. 8.50x5.50x0.75 inches. In Stock.

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Hardcover. Condizione: new. Hardcover. Theory, experiments, computation, and data are considered as the four pillars of science and engineering. Experimental Design for Data Science and Engineering describes efficient statistical methods for making the experiments cheaper and computations faster for extracting valuable information from data and help identify discrepancies in the theory. The book also includes recent advances in experimental designs for dealing with large amounts of observational data.Traditionally the design and analysis of physical and computer experiments are treated differently, but this book attempts to create a unified framework using Gaussian process models. Although optimal designs are formulated using Gaussian process models, the focus is on obtaining practical experimental designs that are robust to model assumptions. A wide variety of topics are covered in the book -- from designs for interpolating or integrating simple functions to designs that are useful for optimizing and calibrating complex computer models. It draws techniques that are spread across the fields of statistics, applied mathematics, operations research, uncertainty quantification, and information theory, and build experimental design as a fundamental data analytic tool for engineering and scientific discoveries.Designs for both computer and physical experiments are discussed in a unified framework.Integrates several concepts from numerical analysis, Monte Carlo methods, sensitivity analysis, optimization, and machine learning with experimental design techniques in statistics.Methods are explained using many real experiments from physical sciences and engineering.Experimental design techniques for analysis and compression of big data are discussed.All the numerical illustrations in the book are reproducible using R and Python codes provided in the authors GitHub site. This book describes efficient statistical methods for making the experiments cheaper and computations faster for extracting valuable information from data and help identify discrepancies in the theory. It also includes recent advances in experimental designs for dealing with large amounts of observational data. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condizione: As New. Unread book in perfect condition.

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

Condizione: New. 2026. 1st Edition. hardcover. . . . . .

Condizione: New. V. Roshan Joseph is A. Russell Chandler III Chair and Professor in the Stewart School of Industrial and Systems Engineering at Georgia Tech. He is an author of more than 100 journal articles and has received many research awards. He is a.

Hardcover. Condizione: Brand New. 256 pages. 9.18x6.12x0.79 inches. In Stock.

Hardcover. Condizione: new. Hardcover. Theory, experiments, computation, and data are considered as the four pillars of science and engineering. Experimental Design for Data Science and Engineering describes efficient statistical methods for making the experiments cheaper and computations faster for extracting valuable information from data and help identify discrepancies in the theory. The book also includes recent advances in experimental designs for dealing with large amounts of observational data.Traditionally the design and analysis of physical and computer experiments are treated differently, but this book attempts to create a unified framework using Gaussian process models. Although optimal designs are formulated using Gaussian process models, the focus is on obtaining practical experimental designs that are robust to model assumptions. A wide variety of topics are covered in the book -- from designs for interpolating or integrating simple functions to designs that are useful for optimizing and calibrating complex computer models. It draws techniques that are spread across the fields of statistics, applied mathematics, operations research, uncertainty quantification, and information theory, and build experimental design as a fundamental data analytic tool for engineering and scientific discoveries.Designs for both computer and physical experiments are discussed in a unified framework.Integrates several concepts from numerical analysis, Monte Carlo methods, sensitivity analysis, optimization, and machine learning with experimental design techniques in statistics.Methods are explained using many real experiments from physical sciences and engineering.Experimental design techniques for analysis and compression of big data are discussed.All the numerical illustrations in the book are reproducible using R and Python codes provided in the authors GitHub site. This book describes efficient statistical methods for making the experiments cheaper and computations faster for extracting valuable information from data and help identify discrepancies in the theory. It also includes recent advances in experimental designs for dealing with large amounts of observational data. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Condizione: New. 2026. 1st Edition. hardcover. . . . . . Books ship from the US and Ireland.

Buch. Condizione: Neu. Neuware - Theory, experiments, computation, and data are considered as the four pillars of science and engineering. Experimental Design for Data Science and Engineering describes efficient statistical methods for making the experiments cheaper and computations faster for extracting valuable information from data and help identify discrepancies in the theory. The book also includes recent advances in experimental designs for dealing with large amounts of observational data.Traditionally the design and analysis of physical and computer experiments are treated differently, but this book attempts to create a unified framework using Gaussian process models. Although optimal designs are formulated using Gaussian process models, the focus is on obtaining practical experimental designs that are robust to model assumptions. A wide variety of topics are covered in the book -- from designs for interpolating or integrating simple functions to designs that are useful for optimizing and calibrating complex computer models. It draws techniques that are spread across the fields of statistics, applied mathematics, operations research, uncertainty quantification, and information theory, and build experimental design as a fundamental data analytic tool for engineering and scientific discoveries. - Designs for both computer and physical experiments are discussed in a unified framework. - Integrates several concepts from numerical analysis, Monte Carlo methods, sensitivity analysis, optimization, and machine learning with experimental design techniques in statistics. - Methods are explained using many real experiments from physical sciences and engineering. - Experimental design techniques for analysis and compression of big data are discussed. - All the numerical illustrations in the book are reproducible using R and Python codes provided in the author's GitHub site.

Hardcover. Condizione: new. Hardcover. Theory, experiments, computation, and data are considered as the four pillars of science and engineering. Experimental Design for Data Science and Engineering describes efficient statistical methods for making the experiments cheaper and computations faster for extracting valuable information from data and help identify discrepancies in the theory. The book also includes recent advances in experimental designs for dealing with large amounts of observational data.Traditionally the design and analysis of physical and computer experiments are treated differently, but this book attempts to create a unified framework using Gaussian process models. Although optimal designs are formulated using Gaussian process models, the focus is on obtaining practical experimental designs that are robust to model assumptions. A wide variety of topics are covered in the book -- from designs for interpolating or integrating simple functions to designs that are useful for optimizing and calibrating complex computer models. It draws techniques that are spread across the fields of statistics, applied mathematics, operations research, uncertainty quantification, and information theory, and build experimental design as a fundamental data analytic tool for engineering and scientific discoveries.Designs for both computer and physical experiments are discussed in a unified framework.Integrates several concepts from numerical analysis, Monte Carlo methods, sensitivity analysis, optimization, and machine learning with experimental design techniques in statistics.Methods are explained using many real experiments from physical sciences and engineering.Experimental design techniques for analysis and compression of big data are discussed.All the numerical illustrations in the book are reproducible using R and Python codes provided in the authors GitHub site. This book describes efficient statistical methods for making the experiments cheaper and computations faster for extracting valuable information from data and help identify discrepancies in the theory. It also includes recent advances in experimental designs for dealing with large amounts of observational data. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.