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Author: Hardeo Sahai
Publisher: Springer Science & Business Media
ISBN: 1461213444
Category : Mathematics
Languages : en
Pages : 766
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Book Description
The analysis of variance (ANOYA) models have become one of the most widely used tools of modern statistics for analyzing multifactor data. The ANOYA models provide versatile statistical tools for studying the relationship between a dependent variable and one or more independent variables. The ANOYA mod els are employed to determine whether different variables interact and which factors or factor combinations are most important. They are appealing because they provide a conceptually simple technique for investigating statistical rela tionships among different independent variables known as factors. Currently there are several texts and monographs available on the sub ject. However, some of them such as those of Scheffe (1959) and Fisher and McDonald (1978), are written for mathematically advanced readers, requiring a good background in calculus, matrix algebra, and statistical theory; whereas others such as Guenther (1964), Huitson (1971), and Dunn and Clark (1987), although they assume only a background in elementary algebra and statistics, treat the subject somewhat scantily and provide only a superficial discussion of the random and mixed effects analysis of variance.
Author: Hardeo Sahai
Publisher: Springer Science & Business Media
ISBN: 1461213444
Category : Mathematics
Languages : en
Pages : 766
Get Book Here
Book Description
The analysis of variance (ANOYA) models have become one of the most widely used tools of modern statistics for analyzing multifactor data. The ANOYA models provide versatile statistical tools for studying the relationship between a dependent variable and one or more independent variables. The ANOYA mod els are employed to determine whether different variables interact and which factors or factor combinations are most important. They are appealing because they provide a conceptually simple technique for investigating statistical rela tionships among different independent variables known as factors. Currently there are several texts and monographs available on the sub ject. However, some of them such as those of Scheffe (1959) and Fisher and McDonald (1978), are written for mathematically advanced readers, requiring a good background in calculus, matrix algebra, and statistical theory; whereas others such as Guenther (1964), Huitson (1971), and Dunn and Clark (1987), although they assume only a background in elementary algebra and statistics, treat the subject somewhat scantily and provide only a superficial discussion of the random and mixed effects analysis of variance.
Author: Lawrence S. Meyers
Publisher: SAGE
ISBN: 9781412904124
Category : Mathematics
Languages : en
Pages : 768
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Book Description
Multivariate designs were once the province of the very few exalted researchers who understood the underlying advanced mathematics. Today, through the sophistication of statistical software packages such as SPSS, virtually all graduate students across the social and behavioural sciences are exposed to the complex multivariate statistical techniques without having to learn the mathematical computations needed to acquire the data output. These students - in psychology, education, political science, etc. - will never be statisticians and appropriately so, their preparation and coursework reflects less of an emphasis on the mathematical complexities of multivariate statistics and more on the analysis and the interpretation of the methods themselves and the actual data output. This book provides full coverage of the wide range of multivariate topics in a conceptual, rather than mathematical, approach. The author gears toward the needs, level of sophistication, and interest in multivariate methodology of students in applied areas that need to focus on design and interpretation rather than the intricacies of specific computations. The book includes: - Coverage of the most widely used multivariate designs: multiple regression, exploratory factor analysis, MANOVA, and structural equation modeling. - Integrated SPSS examples for hands-on learning from one large study (for consistency of application throughout the text). - Examples of written results to enable students to learn how the results of these procedures are communicated. - Practical application of the techniques using contemporary studies that will resonate with students.
Author: Gustav Levine
Publisher: Psychology Press
ISBN:
Category : Computers
Languages : en
Pages : 218
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Book Description
Accompanying CD-ROM contains ... "all of the book's data sets as well as exercises for each chapter."--Page 4 of cover.
Author: Henry Scheffé
Publisher: John Wiley & Sons
ISBN: 9780471345053
Category : Mathematics
Languages : en
Pages : 500
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Book Description
Originally published in 1959, this classic volume has had a major impact on generations of statisticians. Newly issued in the Wiley Classics Series, the book examines the basic theory of analysis of variance by considering several different mathematical models. Part I looks at the theory of fixed-effects models with independent observations of equal variance, while Part II begins to explore the analysis of variance in the case of other models.
Author: Tom King
Publisher: Espresso Tutorials GmbH
ISBN: 3960120672
Category : Computers
Languages : en
Pages : 220
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Book Description
Manufacturing companies need to put a large amount of effort into controlling variances in production. The SAP S/4HANA system provides many tools for highlighting and reviewing these variances. In this book, explore the sources of manufacturing order costs and how they interact to generate variances. Look into target cost versions and learn how different views of variances can give each stakeholder a fuller understanding of non-conformance in manufacturing. Review strategies for setting up the reporting tools to give the most actionable information. Learn some tips for analyzing reporting needs and how to keep the information fresh and meaningful. Understand the interaction between manufacturing orders and cost centers in order to see the big picture of manufacturing performance. Look into the period-end tasks required for order settlement and see how that impacts views of variances. Get an overview of the important configuration tasks. Learn about: - How SAP Manufacturing and Controlling modules interact - Sources of target and actual costs used to determine variances - How manufacturing reporting affects cost center accounting - Strategies for interpreting and managing variances in manufacturing
Author: Gudmund R. Iversen
Publisher: SAGE
ISBN: 9780803930018
Category : Mathematics
Languages : en
Pages : 104
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Book Description
The authors have improved on their widely used first edition by providing updated examples, adding material on how to do ANOVA using statistical packages for microcomputers, linking the use of ANOVA to regression analysis, and enchancing their discussion on using ANOVA for experimentally gathered data.
Author: Sharon Lawner Weinberg
Publisher: Cambridge University Press
ISBN: 0521899222
Category : Mathematics
Languages : en
Pages : 13
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Book Description
Applied statistics text updated to be consistent with SPSS version 15, ideal for classroom use or self study.
Author: Paul C. Dinsmore
Publisher: Amacom Books
ISBN: 9780814429242
Category : Business & Economics
Languages : en
Pages : 542
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Book Description
The authoritative guide to project management...completely revised to meet the accelerating pace of today''s project environment.
Author: Ronald Christensen
Publisher: CRC Press
ISBN: 9780412062919
Category : Mathematics
Languages : en
Pages : 608
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Book Description
This text presents a comprehensive treatment of basic statistical methods and their applications. It focuses on the analysis of variance and regression, but also addressing basic ideas in experimental design and count data. The book has four connecting themes: similarity of inferential procedures, balanced one-way analysis of variance, comparison of models, and checking assumptions. Most inferential procedures are based on identifying a scalar parameter of interest, estimating that parameter, obtaining the standard error of the estimate, and identifying the appropriate reference distribution. Given these items, the inferential procedures are identical for various parameters. Balanced one-way analysis of variance has a simple, intuitive interpretation in terms of comparing the sample variance of the group means with the mean of the sample variance for each group. All balanced analysis of variance problems are considered in terms of computing sample variances for various group means. Comparing different models provides a structure for examining both balanced and unbalanced analysis of variance problems and regression problems. Checking assumptions is presented as a crucial part of every statistical analysis. Examples using real data from a wide variety of fields are used to motivate theory. Christensen consistently examines residual plots and presents alternative analyses using different transformation and case deletions. Detailed examination of interactions, three factor analysis of variance, and a split-plot design with four factors are included. The numerous exercises emphasize analysis of real data. Senior undergraduate and graduate students in statistics and graduate students in other disciplines using analysis of variance, design of experiments, or regression analysis will find this book useful.
Author: Harold R. Lindman
Publisher: Springer Science & Business Media
ISBN: 1461397227
Category : Mathematics
Languages : en
Pages : 532
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Book Description
As an introductory textbook on the analysis of variance or a reference for the researcher, this text stresses applications rather than theory, but gives enough theory to enable the reader to apply the methods intelligently rather than mechanically. Comprehensive, and covering the important techniques in the field, including new methods of post hoc testing. The relationships between different research designs are emphasized, and these relationships are exploited to develop general principles which are generalized to the analyses of a large number of seemingly differentdesigns. Primarily for graduate students in any field where statistics are used.
