Analysis of Variance and Functional Measurement
Analysis of Variance and Functional Measurement

Author: David J. Weiss

Publisher: Oxford University Press

Published: 2006

Total Pages: 278

ISBN-13: 0195183150

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This book is a clear and straightforward guide to analysis of variance, the backbone of experimental research. It will show you how to interpret statistical results and translate them into prose that will clearly tell your audience what your data is saying. To help you become familiar with the techniques used in analysis of variance, there are plenty of end-of-chapter practice problems with suggested answers. As life in the laboratory doesnt always follow a script, there are both new and established techniques for coping with situations that deviate from the norm. Data analysis is not a closed subject, so there are pros and cons for the varied situations you will encounter. The final chapter gives the first elementary presentation of functional measurement, or information integration theory, a methodology built upon analysis of variance that is a powerful technique for studying cognitive processes. The accompanying CD contains CALSTAT, analysis of variance software that is easy to use (really!). In addition to programs for standard analysis, the software includes several specialized routines that have heretofore been presented only in journals. Analysis of Variance is an important resource for students and professionals in the social, behavioral, and neurosciences.

Analysis of Variance for Functional Data
Analysis of Variance for Functional Data

Author: Jin-Ting Zhang

Publisher: CRC Press

Published: 2013-06-18

Total Pages: 406

ISBN-13: 1439862745

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Despite research interest in functional data analysis in the last three decades, few books are available on the subject. Filling this gap, Analysis of Variance for Functional Data presents up-to-date hypothesis testing methods for functional data analysis. The book covers the reconstruction of functional observations, functional ANOVA, functional l

Learning Statistics with R
Learning Statistics with R

Author: Daniel Navarro

Publisher: Lulu.com

Published: 2013-01-13

Total Pages: 617

ISBN-13: 1326189727

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"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. 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. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com

Experimental Design and the Analysis of Variance
Experimental Design and the Analysis of Variance

Author: Robert K. Leik

Publisher: SAGE Publications

Published: 1997-04-19

Total Pages: 209

ISBN-13: 1452250359

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Why is this Book a Useful Supplement for Your Statistics Course? Most core statistics texts cover subjects like analysis of variance and regression, but not in much detail. This book, as part of our Series in Research Methods and Statistics, provides you with the flexibility to cover ANOVA more thoroughly, but without financially overburdening your students.

Understanding Statistics and Experimental Design
Understanding Statistics and Experimental Design

Author: Michael H. Herzog

Publisher: Springer

Published: 2019-08-13

Total Pages: 146

ISBN-13: 3030034992

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This open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings. Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and work out their statistical principles. Part III provides insight into meta-statistics (statistics of statistics) and demonstrates why experiments often do not replicate. Finally, the textbook shows how complex statistics can be avoided by using clever experimental design. Both non-scientists and students in Biology, Biomedicine and Engineering will benefit from the book by learning the statistical basis of scientific claims and by discovering ways to evaluate the quality of scientific reports in academic journals and news outlets.

ANOVA
ANOVA

Author: Ellen R. Girden

Publisher: SAGE

Published: 1992

Total Pages: 88

ISBN-13: 9780803942578

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Focusing on situations in which analysis of variance (ANOVA) involving the repeated measurement of separate groups of individuals is needed, Girden reveals the advantages, disadvantages, and counterbalancing issues of repeated measures situations. Using additive and nonadditive models to guide the analysis in each chapter, the book covers such topics as the rationale for partitioning the sum of squares, detailed analyses to facilitate the interpretation of computer printouts, the rationale for the F ratios in terms of expected means squares, validity assumptions for sphericity or circularity and approximate tests to perform when sphericity is not met.

Encyclopedia of Research Design
Encyclopedia of Research Design

Author: Neil J. Salkind

Publisher: SAGE

Published: 2010-06-22

Total Pages: 1779

ISBN-13: 1412961270

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"Comprising more than 500 entries, the Encyclopedia of Research Design explains how to make decisions about research design, undertake research projects in an ethical manner, interpret and draw valid inferences from data, and evaluate experiment design strategies and results. Two additional features carry this encyclopedia far above other works in the field: bibliographic entries devoted to significant articles in the history of research design and reviews of contemporary tools, such as software and statistical procedures, used to analyze results. It covers the spectrum of research design strategies, from material presented in introductory classes to topics necessary in graduate research; it addresses cross- and multidisciplinary research needs, with many examples drawn from the social and behavioral sciences, neurosciences, and biomedical and life sciences; it provides summaries of advantages and disadvantages of often-used strategies; and it uses hundreds of sample tables, figures, and equations based on real-life cases."--Publisher's description.

The Analysis of Variance
The Analysis of Variance

Author: Henry Scheffé

Publisher: John Wiley & Sons

Published: 1999-03-05

Total Pages: 500

ISBN-13: 9780471345053

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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.

Psychophysical Judgment and Measurement
Psychophysical Judgment and Measurement

Author: Edward Carterette

Publisher: Elsevier

Published: 2012-12-02

Total Pages: 589

ISBN-13: 0323145345

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Handbook of Perception, Volume II: Psychophysical Judgment and Measurement brings together a very large, diverse, and widely scattered literature on human perception, with emphasis on psychophysical judgement and measurement. The book reviews the history of research on choice, judgement, and measurement in order to provide a background for contemporary work. This volume is organized into five sections encompassing 14 chapters and begins with a historical background on psychophysics and the evolution of thinking about the central measurement problem in judgement. The basic psychological context in which choice and judgement occur is considered next, touching on topics such as the problem of information selection and the sources of bias and variability in judgemental processes in relation to memory. The chapters that follow discuss the theoretical frame of measurement models and their applications. In particular, examples of algebraic fundamental measurement, algebraic derived measurement, and probabilistic derived measurement are given. The book also introduces the reader to various psychophysical scaling methods and theories of scaling. This book will serve as a basic source and reference work for psychologists and natural scientists, as well as for anyone in the arts or sciences or those who are interested in human perception.