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Sinopsis
This compact, entry-level Handbook equips applied practitioners to choose and use core models for real-world data - with R and SAS.
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Jamie D. Riggs is an adjunct lecturer in the Predictive Analytics program at Northwestern University, Illinois. She specializes in the statistical issues of solar system cratering processes, solar physics, and galactic dynamics, and has collaborated with researchers at the Los Alamos National Laboratory, New Mexico and the Southwest Research Institute, Texas. She has held technical and managerial positions at Sun Microsystems, Inc., National Oceanic and Atmospheric Administration, and the Boeing Company, where she applied advanced statistical designs and analyses to manufacturing and business problems. She is the Solar System and Planetary Sciences Section Head of the International Astrostatistics Association.
Trent L. Lalonde is Associate Professor of Applied Statistics at the University of Northern Colorado, and Director of the University's Research Consulting Lab. He has spent a number of years designing and teaching graduate courses covering statistical methods for students in diverse areas such as special education, psychological sciences, and public health. In addition, he has helped direct dissertations in these areas, and has consulted with numerous faculty on publications and funding proposals. He has received awards for both instruction and advising, and has Chaired the Applied Public Health Statistics section of the American Public Health Association.
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Handbook for Applied Modeling: Non-Gaussian and Correlated Data
Publicado por
Cambridge University Press, 2017
ISBN 10: 1316601056
ISBN 13: 9781316601051
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Librería: Romtrade Corp., STERLING HEIGHTS, MI, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide. Nº de ref. del artículo: ABNR-94029
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Handbook for Applied Modeling: Non-Gaussian and Correlated Data
Publicado por
Cambridge University Press, 2017
ISBN 10: 1316601056
ISBN 13: 9781316601051
Nuevo
Tapa blanda
Librería: Romtrade Corp., STERLING HEIGHTS, MI, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide. Nº de ref. del artículo: ABNR-98707
Cantidad disponible: 1 disponibles
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Handbook for Applied Modeling: Non-Gaussian and Correlated Data
Publicado por
Cambridge University Press, 2017
ISBN 10: 1316601056
ISBN 13: 9781316601051
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Librería: Basi6 International, Irving, TX, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Nº de ref. del artículo: ABEOCT25-151885
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Handbook for Applied Modeling: Non-Gaussian and Correlated Data
Publicado por
Cambridge University Press, 2017
ISBN 10: 1316601056
ISBN 13: 9781316601051
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Handbook for Applied Modeling : Non-Gaussian and Correlated Data
Publicado por
Cambridge University Press, 2017
ISBN 10: 1316601056
ISBN 13: 9781316601051
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Handbook for Applied Modeling: Non-Gaussian and Correlated Data
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: FM-9781316601051
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Handbook for Applied Modeling: Non-Gaussian and Correlated Data
Publicado por
Cambridge University Press, 2017
ISBN 10: 1316601056
ISBN 13: 9781316601051
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Librería: ALLBOOKS1, Direk, SA, Australia
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Handbook for Applied Modeling: Non-Gaussian and Correlated Data (Paperback)
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Cambridge University Press, Cambridge, 2017
ISBN 10: 1316601056
ISBN 13: 9781316601051
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: new. Paperback. Designed for the applied practitioner, this book is a compact, entry-level guide to modeling and analyzing non-Gaussian and correlated data. Many practitioners work with data that fail the assumptions of the common linear regression models, necessitating more advanced modeling techniques. This Handbook presents clearly explained modeling options for such situations, along with extensive example data analyses. The book explains core models such as logistic regression, count regression, longitudinal regression, survival analysis, and structural equation modelling without relying on mathematical derivations. All data analyses are performed on real and publicly available data sets, which are revisited multiple times to show differing results using various modeling options. Common pitfalls, data issues, and interpretation of model results are also addressed. Programs in both R and SAS are made available for all results presented in the text so that readers can emulate and adapt analyses for their own data analysis needs. Data, R, and SAS scripts can be found online at Designed for the applied practitioner, this book is a compact, entry-level guide to modeling and analyzing data that fail idealized assumptions. It explains and demonstrates core techniques, common pitfalls and data issues, and interpretation of model results, all with a focus on application, utility, and real-life data. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9781316601051
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Handbook for Applied Modeling: Non-Gaussian and Correlated Data
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Handbook for Applied Modeling : Non-Gaussian and Correlated Data
Publicado por
Cambridge University Press, 2017
ISBN 10: 1316601056
ISBN 13: 9781316601051
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 28630527
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