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Analysis of Covariance
This series of methodological works provides introductory explanations and demonstration of various data analysis techniques applicable to the social sciences. Designed for readers with a limited background in statistics or mathematics, this series aims to make the assumptions and practices of quantitative analysis more readily accessible.
The Analysis of Covariance and Alternatives
A complete guide to cutting-edge techniques and best practices for applying covariance analysis methods The Second Edition of Analysis of Covariance and Alternatives sheds new light on its topic, offering in-depth discussions of underlying assumptions, comprehensive interpretations of results, and comparisons of distinct approaches. The book has been extensively revised and updated to feature an in-depth review of prerequisites and the latest developments in the field. The author begins with a discussion of essential topics relating to experimental design and analysis, including analysis of variance, multiple regression, effect size measures and newly developed methods of communicating stati...
Analysis of Variance and Covariance
Analysis of variance (ANOVA) is a core technique for analysing data in the Life Sciences. This reference book bridges the gap between statistical theory and practical data analysis by presenting a comprehensive set of tables for all standard models of analysis of variance and covariance with up to three treatment factors. The book will serve as a tool to help post-graduates and professionals define their hypotheses, design appropriate experiments, translate them into a statistical model, validate the output from statistics packages and verify results. The systematic layout makes it easy for readers to identify which types of model best fit the themes they are investigating, and to evaluate the strengths and weaknesses of alternative experimental designs. In addition, a concise introduction to the principles of analysis of variance and covariance is provided, alongside worked examples illustrating issues and decisions faced by analysts.
Analysis of Covariance:
The Analysis of Covariance is a wonderful, clever, perhaps ingenious and inspirational technique for using statistical projections to adjust predictor variables in groups which are biased due to inequities in variables initially used to create these groups. In Biology, Psychology, Sociology, Business, Psycho-Dynamics in Human Relations, and Medicine, for example, groups used in experiments are often not equated on initial variables which can be experimentally controlled. Therefore, these inequities on initial variables ordinarily would bias results when different treatments are applied to these groups. However, using Analysis of Covariance, through a fascinating statistical application of pr...
Analysis of Messy Data, Volume III
Analysis of covariance is a very useful but often misunderstood methodology for analyzing data where important characteristics of the experimental units are measured but not included as factors in the design. Analysis of Messy Data, Volume 3: Analysis of Covariance takes the unique approach of treating the analysis of covariance problem by looking
Categorical Data Analysis Using the SAS System
Discusses hypothesis testing strategies for the assessment of association in contingency tables and sets of contingency tables. Also discusses various modeling strategies available for describing the nature of the association between a categorical outcome measure and a set of explanatory variables.
Eddy Covariance
This highly practical handbook is an exhaustive treatment of eddy covariance measurement that will be of keen interest to scientists who are not necessarily specialists in micrometeorology. The chapters cover measuring fluxes using eddy covariance technique, from the tower installation and system dimensioning to data collection, correction and analysis. With a state-of-the-art perspective, the authors examine the latest techniques and address the most up-to-date methods for data processing and quality control. The chapters provide answers to data treatment problems including data filtering, footprint analysis, data gap filling, uncertainty evaluation, and flux separation, among others. The a...
Calculation and Interpretation of Analysis of Variance and Covariance
Single criterion of classification; Two criteria of classification; Three or more criteria of classification; Analysis of covariance; Table of values of f.
