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Practical data analysis with JMP /

This book uses the powerful interactive and visual approach of JMP to introduce readers to the logic and methods of statistical thinking and data analysis. It enables you to discriminate among and to use fundamental techniques of analysis, enabling you to engage in statistical thinking by analyzing...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Carver, Robert H.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cary, NC : SAS Institute, ©2014.
Edición:2nd ed.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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245 1 0 |a Practical data analysis with JMP /  |c Robert H. Carver. 
250 |a 2nd ed. 
260 |a Cary, NC :  |b SAS Institute,  |c ©2014. 
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520 |a This book uses the powerful interactive and visual approach of JMP to introduce readers to the logic and methods of statistical thinking and data analysis. It enables you to discriminate among and to use fundamental techniques of analysis, enabling you to engage in statistical thinking by analyzing real-world problems. "Application Scenarios" at the end of each chapter challenge you to put your knowledge and skills to use with data sets that go beyond mere repetition of chapter examples, and three new review chapters help readers integrate ideas and techniques. In addition, the scope and sequence of the chapters have been updated with more coverage of data management and analysis of data. The book can stand on its own as a learning resource for professionals or be used to supplement a standard college-level introduction-to-statistics textbook. Reflective of the broad applicability of statistical reasoning, the problems included inthe book come from a wide variety of disciplines, including engineering, life sciences, business, economics, among others, and include a number of international and historical examples. --  |c Edited summary from back cover 
505 0 |a Getting started : data analysis with JMP -- Data sources and structures -- Describing a single variable -- Describing two variables at a time -- Review of descriptive statistics -- Elementary probability and discrete distributions -- The normal model -- Sampling and sampling distributions -- Review of probability and probabilistic sampling -- Inference for a single categorical variable -- Inference for a single continuous variable -- Chi-square tests -- Two-sample inference for a continuous variable -- Analysis of variance -- Simple linear regression inference -- Residuals analysis and estimation -- Review of univariate and bivariate inference -- Multiple regression -- Categorical, curvilinear, and non-linear regression models -- Basic forecasting techniques -- Elements of experimental design -- Quality improvement. 
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