Name: Data Management and Analysis Using JMP: Health Care Case Studies (en Inglés)
Price: 222.18 PEN
Availability: InStock
Author: Oppenlander, Jane E. ; Schaffer, Patricia
ISBN: 9781629603858

portada Data Management and Analysis Using JMP: Health Care Case Studies (en Inglés)

Formato

Libro Físico

Autor

Jane E. Oppenlander

Patricia Schaffer

Editorial

SAS Institute

Idioma

Inglés

N° páginas

250

Encuadernación

Tapa Blanda

Dimensiones

23.5 x 19.1 x 1.3 cm

Peso

0.44 kg.

ISBN13

9781629603858

Categorías

Software empresarial
Software de matemáticas y estadísticas
Programación informática - desarrollo de software

Data Management and Analysis Using JMP: Health Care Case Studies (en Inglés)

Jane E. Oppenlander (Autor) · Patricia Schaffer (Autor) · SAS Institute · Tapa Blanda

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S/ 444,37

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Origen: Estados Unidos (Costos de importación incluídos en el precio)

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Reseña del libro "Data Management and Analysis Using JMP: Health Care Case Studies (en Inglés)"

A holistic, step-by-step approach to analyzing health care data! Written for both beginner and intermediate JMP users working in or studying health care, Data Management and Analysis Using JMP: Health Care Case Studies bridges the gap between taking traditional statistics courses and successfully applying statistical analysis in the workplace. Authors Jane Oppenlander and Patricia Schaffer begin by illustrating techniques to prepare data for analysis, followed by presenting effective methods to summarize, visualize, and analyze data. The statistical analysis methods covered in the book are the foundational techniques commonly applied to meet regulatory, operational, budgeting, and research needs in the health care field. This example-driven book shows practitioners how to solve real-world problems by using an approach that includes problem definition, data management, selecting the appropriate analysis methods, step-by-step JMP instructions, and interpreting statistical results in context. Practical strategies for selecting appropriate statistical methods, remediating data anomalies, and interpreting statistical results in the domain context are emphasized. The cases presented in Data Management and Analysis Using JMP use multiple statistical methods. A progression of methods--from univariate to multivariate--is employed, illustrating a logical approach to problem-solving. Much of the data used in these cases is open source and drawn from a variety of health care settings. The book offers a welcome guide to working professionals as well as students studying statistics in health care-related fields.