Systematic treatment of the commonly employed crossed and nested classification models used in analysis of variance designs with a detailed and thorough discussion of certain random effects models not commonly found in texts at the introductory or intermediate level. It also includes numerical examples to analyze data from a wide variety of disciplines as well as any worked examples containing computer outputs from standard software packages such as SAS, SPSS, and BMDP for each numerical example.
Analysis of Variance for Random Models: Theory, Methods, Applications, and Data Analysis. Unbalanced data : theory, methods, applications, and data...
"Choice "This is a very comprehensive text, aimed at both students studying linear-model theory and practicing statisticians who require an understanding of the model-fitting procedures incorporated in statistical packages?This book should ...
... of Data in Clinical Trials "' McLACHLAN - Discriminant Analysis and Statistical Pattern Recognition McLACHLAN, DO, and AMBROISE ' Analyzing Microarray Gene Expression Data McLACHLAN and KRISHNAN - The EM Algorithm and Extensions ...
Steinmetz, V.; Sevila, F.; Bellon-Maurel, V. A Methodology for Sensor Fusion Design: Application to Fruit Quality Assessment. J. Agric. Eng. Res. ... Based Data Fusion for Machine Learning, Springer Berlin Heidelberg, 2011. 97.
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.
Dieser Band beschreibt allgemeine Verfahren zur Abschätzung und Hypothesenprüfung für lineare statistische Modelle. Besonderen Wert legt das Buch auf die Interpretation unausgeglichener Daten.
The book carefully analyzes small data sets by using tools that are easily scaled to big data. The tools also apply to small relevant data sets that are extracted from big data.
Chow, G. C. (1976). A Note on the Derivation of Theil's BLUS Residuals. Econometrica, 44:609–610. Christensen, R. (1987). Plane Answers to Complex Questions. Springer, New York. Christensen, R. (2011). Plane Answers to Complex Questions ...
A reference devoted to the discussion of analysis of variance (ANOVA) techniques. It presents ANOVA as a research design, a collection of statistical models, an analysis model, and an arithmetic summary of data.
After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book.