Cognitive Learning and Memory in Children

Progress in Cognitive Development Research

Author: M. Pressley,C.J. Brainerd

Publisher: Springer Science & Business Media

ISBN: 1461395445

Category: Psychology

Page: 250

View: 8965

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For some time now, the study of cognitive development has been far and away the most active discipline within developmental psychology. Although there would be much disagreement as to the exact proportion of papers published in developmental journals that could be considered cognitive, 50% seems like a conservative estimate. Hence, a series of scholarly books devoted to work in cognitive development is especially appropriate at this time. The Springer Series in Cognitive Development contains two basic types of books, namely, edited collections of original chapters by several authors, and original volumes written by one author or a small group of authors. The flagship for the Springer Series is a serial pUblication of the" advances" type, carrying the subtitle Progress in Cognitive Development Research. Each volume in the Progress sequence is strongly thematic, in that it is limited to some well-defined domain of cognitive-developmental research (e. g. , logical and mathematical development, development of learning). All Progress volumes will be edited collections. Editors of such collections, upon consultation with the Series Editor, may elect to have their books published either as contributions to the Progress sequence or as separate volumes. All books written by one author or a small group of authors are being published as separate volumes within the series. A fairly broad definition of cognitive development is being used in the selection of books for this series.

Applied Multivariate Statistics for the Social Sciences

Author: James Paul Stevens

Publisher: Taylor & Francis

ISBN: 0805859012

Category: Social Science

Page: 651

View: 7615

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This best-selling text is written for those who use, rather than develop statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than on proving results. Helpful narrative and numerous examples enhance understanding and a chapter on matrix algebra serves as a review. Annotated printouts from SPSS and SAS indicate what the numbers mean and encourage interpretation of the results. In addition to demonstrating how to use these packages, the author stresses the importance of checking the data, assessing the assumptions, and ensuring adequate sample size by providing guidelines so that the results can be generalized. The book is noted for its extensive applied coverage of MANOVA, its emphasis on statistical power, and numerous exercises including answers to half. The new edition features: New chapters on Hierarchical Linear Modeling (Ch. 15) and Structural Equation Modeling (Ch. 16) New exercises that feature recent journal articles to demonstrate the actual use of multiple regression (Ch. 3), MANOVA (Ch. 5), and repeated measures (Ch. 13) A new appendix on the analysis of correlated observations (Ch. 6) Expanded discussions on obtaining non-orthogonal contrasts in repeated measures designs with SPSS and how to make the identification of cell ID easier in log linear analysis in 4 or 5 way designs Updated versions of SPSS (15.0) and SAS (8.0) are used throughout the text and introduced in chapter 1 A book website with data sets and more. Ideal for courses on multivariate statistics found in psychology, education, sociology, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods. Prerequisites include a course on factorial ANOVA and covariance. Working knowledge of matrix algebra is not assumed.

Research Methodology: A Guide for Researchers In Agricultural Science, Social Science and Other Related Fields

Author: Pradip Kumar Sahu

Publisher: Springer Science & Business Media

ISBN: 8132210204

Category: Technology & Engineering

Page: 432

View: 6652

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This book is the outcome of more than 20 years of experience of the author in teaching and research field. The wider scope and coverage of the book will help not only the students/ researchers/professionals in the field of agriculture and allied disciplines, but also the researchers and practitioners in other fields. Written in simple and lucid language, the book would appeal to all those who are meant to be benefitted out of it. All efforts have been made to present "RESEARCH", its meaning, intention and usefulness. The book reflects current methodological techniques used in interdisciplinary research, as illustrated with many relevant worked out examples. Designing of research programme, selection of variables, collection of data and their analysis to interpret the data are discussed extensively. Statistical tools are complemented with real-life examples, making the otherwise complicated subject like statistics seem simpler. Attempts have been made to demonstrate how a user can solve the problems using simple computer-oriented programme. Emphasis is placed not only on solving the problems in various fields but also on drawing inferences from the problems. The importance of instruments and computers in research processes and statistical analyses along with their misuse/incorrect use is also discussed to make the user aware about the correct use of specific technique. In all the chapters, theories are combined with examples, and steps are enumerated to follow the correct use of the available packages like MSEXCELL, SPSS, SPAR1, SAS etc. Utmost care has been taken to present varied range of research problems along with their solutions in agriculture and allied fields which would be of immense use to readers.

Multivariate Analysis Techniques in Social Science Research

From Problem to Analysis

Author: J. J. A. Tacq,Professor Jacques Tacq

Publisher: SAGE

ISBN: 9781446237410

Category:

Page: 432

View: 5314

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Unlike most statistical texts, this book breathes real life into multivariate analysis. Starting with a range of actual research examples in the social sciences, it demonstrates how to make the most appropriate choice of technique. The examples are drawn from a broad spectrum of disciplines including: sociology, psychology, economics, political science and international comparative research.

Applied Multivariate Statistics for the Social Sciences

Analyses with SAS and IBM’s SPSS, Sixth Edition

Author: Keenan A. Pituch,James P. Stevens

Publisher: Routledge

ISBN: 1317805917

Category: Psychology

Page: 814

View: 1744

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Now in its 6th edition, the authoritative textbook Applied Multivariate Statistics for the Social Sciences, continues to provide advanced students with a practical and conceptual understanding of statistical procedures through examples and data-sets from actual research studies. With the added expertise of co-author Keenan Pituch (University of Texas-Austin), this 6th edition retains many key features of the previous editions, including its breadth and depth of coverage, a review chapter on matrix algebra, applied coverage of MANOVA, and emphasis on statistical power. In this new edition, the authors continue to provide practical guidelines for checking the data, assessing assumptions, interpreting, and reporting the results to help students analyze data from their own research confidently and professionally. Features new to this edition include: NEW chapter on Logistic Regression (Ch. 11) that helps readers understand and use this very flexible and widely used procedure NEW chapter on Multivariate Multilevel Modeling (Ch. 14) that helps readers understand the benefits of this "newer" procedure and how it can be used in conventional and multilevel settings NEW Example Results Section write-ups that illustrate how results should be presented in research papers and journal articles NEW coverage of missing data (Ch. 1) to help students understand and address problems associated with incomplete data Completely re-written chapters on Exploratory Factor Analysis (Ch. 9), Hierarchical Linear Modeling (Ch. 13), and Structural Equation Modeling (Ch. 16) with increased focus on understanding models and interpreting results NEW analysis summaries, inclusion of more syntax explanations, and reduction in the number of SPSS/SAS dialogue boxes to guide students through data analysis in a more streamlined and direct approach Updated syntax to reflect newest versions of IBM SPSS (21) /SAS (9.3) A free online resources site at www.routledge.com/9780415836661 with data sets and syntax from the text, additional data sets, and instructor’s resources (including PowerPoint lecture slides for select chapters, a conversion guide for 5th edition adopters, and answers to exercises). Ideal for advanced graduate-level courses in education, psychology, and other social sciences in which multivariate statistics, advanced statistics, or quantitative techniques courses are taught, this book also appeals to practicing researchers as a valuable reference. Pre-requisites include a course on factorial ANOVA and covariance; however, a working knowledge of matrix algebra is not assumed.

Basic Statistics in Multivariate Analysis

Author: Karen A. Randolph,Laura L. Myers

Publisher: Oxford University Press

ISBN: 0199764042

Category: Social Science

Page: 213

View: 8562

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This pocket guide introduces readers to linear regression analysis, analysis of variance and covariance, and path analysis with an emphasis on the basic statistics. It prepares doctoral students and early career social work researchers with limited statistics exposure in the use of multivariate methods by providing an easy-to-understand presentation.

Handbook of Parametric and Nonparametric Statistical Procedures

Fourth Edition

Author: David Sheskin

Publisher: Chapman and Hall/CRC

ISBN: N.A

Category: Mathematics

Page: 1736

View: 4356

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The fourth edition of the popular Handbook of Parametric and Nonparametric Statistical Procedures covers 160 of the most commonly used parametric and nonparametric statistical procedures encountered in theory and in practice. Featuring 26 new statistical tests and examples as well as 55 new figures, this edition provides new material on regression diagnostics, including the Durbin-Watson test. The book provides a new section on multivariate analysis with additional information on matrix algebra, uses of Hotellings T2, and multivariate analysis of variance and covariance. Sections on medical statistics, clinical trials, survival analysis, and analysis of censored data are also presented in this edition.

The Reviewer’s Guide to Quantitative Methods in the Social Sciences

Author: Gregory R. Hancock,Ralph O. Mueller

Publisher: Routledge

ISBN: 1135172994

Category: Education

Page: 448

View: 5942

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The Reviewer’s Guide is designed for reviewers of research manuscripts and proposals in the social and behavioral sciences, and beyond. Its uniquely structured chapters address traditional and emerging quantitative methods of data analysis.

JMP for Basic Univariate and Multivariate Statistics

Methods for Researchers and Social Scientists, Second Edition

Author: Ann Lehman,Norm O'Rourke,Larry Hatcher,Edward Stepanski

Publisher: SAS Institute

ISBN: 1612906036

Category: Computers

Page: 558

View: 5790

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Learn how to manage JMP data and perform the statistical analyses most commonly used in research in the social sciences and other fields with JMP for Basic Univariate and Multivariate Statistics: Methods for Researchers and Social Scientists, Second Edition. Updated for JMP 10 and including new features on the statistical platforms, this book offers clearly written instructions to guide you through the basic concepts of research and data analysis, enabling you to easily perform statistical analyses and solve problems in real-world research. Step by step, you'll discover how to obtain descriptive and inferential statistics, summarize results clearly in a way that is suitable for publication, perform a wide range of JMP analyses, interpret the results, and more. Topics include screening data for errors selecting subsets computing the coefficient alpha reliability index (Cronbach's alpha) for a multiple-item scale performing bivariate analyses for all types of variables performing a one-way analysis of variance (ANOVA), multiple regression, and a one-way multivariate analysis of variance (MANOVA) Advanced topics include analyzing models with interactions and repeated measures. There is also comprehensive coverage of principle components with emphasis on graphical interpretation. This user-friendly book introduces researchers and students of the social sciences to JMP and to elementary statistical procedures, while the more advanced statistical procedures that are presented make it an invaluable reference guide for experienced researchers as well.

Multivariate Analysis for the Biobehavioral and Social Sciences

A Graphical Approach

Author: Bruce L. Brown,Suzanne B. Hendrix,Dawson W. Hedges,Timothy B. Smith

Publisher: John Wiley & Sons

ISBN: 1118131614

Category: Mathematics

Page: 496

View: 7259

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An insightful guide to understanding and visualizing multivariatestatistics using SAS®, STATA®, and SPSS® Multivariate Analysis for the Biobehavioral and Social Sciences:A Graphical Approach outlines the essential multivariate methodsfor understanding data in the social and biobehavioral sciences.Using real-world data and the latest software applications, thebook addresses the topic in a comprehensible and hands-on manner,making complex mathematical concepts accessible to readers. The authors promote the importance of clear, well-designedgraphics in the scientific process, with visual representationsaccompanying the presented classical multivariate statisticalmethods . The book begins with a preparatory review of univariatestatistical methods recast in matrix notation, followed by anaccessible introduction to matrix algebra. Subsequent chaptersexplore fundamental multivariate methods and related key concepts,including: Factor analysis and related methods Multivariate graphics Canonical correlation Hotelling's T-squared Multivariate analysis of variance (MANOVA) Multiple regression and the general linear model (GLM) Each topic is introduced with a research-publication case studythat demonstrates its real-world value. Next, the question "how doyou do that?" is addressed with a complete, yet simplified,demonstration of the mathematics and concepts of the method.Finally, the authors show how the analysis of the data is performedusing Stata®, SAS®, and SPSS®. The discussedapproaches are also applicable to a wide variety of modernextensions of multivariate methods as well as modern univariateregression methods. Chapters conclude with conceptual questionsabout the meaning of each method; computational questions that testthe reader's ability to carry out the procedures on simpledatasets; and data analysis questions for the use of the discussedsoftware packages. Multivariate Analysis for the Biobehavioral and Social Sciencesis an excellent book for behavioral, health, and social sciencecourses on multivariate statistics at the graduate level. The bookalso serves as a valuable reference for professionals andresearchers in the social, behavioral, and health sciences whowould like to learn more about multivariate analysis and itsrelevant applications.

The Psychology Research Handbook

A Guide for Graduate Students and Research Assistants

Author: Frederick T. L. Leong,James T. Austin

Publisher: SAGE

ISBN: 0761930221

Category: Psychology

Page: 516

View: 4916

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A comprehensive, easy-to-understand guide to the entire research process, this book quickly and efficiently equips advanced students and research assistants to conduct a full-scale investigation. The book is organized around the idea of a 'research script' that is, it follows the standard mode of research planning and design, data collection and analysis, and results writing. The volume contains 35 chapters, some co-authored by advanced graduate students who give their fellow students a touch of the 'real world' adding to the clarity and practicality of many chapters.

Neural Networks

An Introductory Guide for Social Scientists

Author: G David Garson

Publisher: SAGE

ISBN: 0761957308

Category: Social Science

Page: 194

View: 1863

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This book provides the first accessible introduction to neural network analysis as a methodological strategy for social scientists. The author details numerous studies and examples which illustrate the advantages of neural network analysis over other quantitative and modelling methods in widespread use. Methods are presented in an accessible style.

Research, Actionable Knowledge, and Social Change

Reclaiming Social Responsibility Through Research Partnerships

Author: Edward P. St. John

Publisher: Stylus Publishing, LLC

ISBN: 1579227376

Category: Education

Page: 276

View: 557

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A professional text written for social science researchers and practitioners, Research, Actionable Knowledge and Social Change provides strategies and frameworks for using social science research to engage in critical social and educational problem solving. Combining the best practices of critical analysis and traditional research methods, this professional text offers guidance for using the Action Inquiry Model (AIM), a transformative model that explains how to successfully conduct action-oriented research in a multitude of professional service organizations. The aim of the text is to encourage a new generation of research-based partnerships reforms that promote equity and access for underserved populations. Topics discussed include: • The historical precedents for universities engaged in social change • The limitations of current social science theory and methods • The critical-empirical approach to social research • The issues relating to social justice within the policy decision process • The use of social research to integrate an emphasis of social justice into economic and policy decision making Research, Actionable Knowledge and Social Change does not propose different foundations for social research, but rather argues that it is necessary to reconsider how to work with theory and research methods to inform change. This text can also be used by students enrolled in graduate and Ed.D/Ph.D Higher Education Leadership programs and graduate programs across professional fields including K-12, public administration, sociology, health, cultural studies, organizational development and organizational theory. It further offers students guidance for research design and dissertation research.

Using R With Multivariate Statistics

Author: Randall E. Schumacker

Publisher: SAGE Publications

ISBN: 1483377989

Category: Social Science

Page: 408

View: 4391

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Using R with Multivariate Statistics by Randall E. Schumacker is a quick guide to using R, free-access software available for Windows and Mac operating systems that allows users to customize statistical analysis. Designed to serve as a companion to a more comprehensive text on multivariate statistics, this book helps students and researchers in the social and behavioral sciences get up to speed with using R. It provides data analysis examples, R code, computer output, and explanation of results for every multivariate statistical application included. In addition, R code for some of the data set examples used in more comprehensive texts is included, so students can run examples in R and compare results to those obtained using SAS, SPSS, or STATA. A unique feature of the book is the photographs and biographies of famous persons in the field of multivariate statistics.

Analysis of Multivariate Social Science Data, Second Edition

Author: David J. Bartholomew,Fiona Steele,Jane Galbraith,Irini Moustaki

Publisher: CRC Press

ISBN: 1584889616

Category: Mathematics

Page: 384

View: 5310

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Drawing on the authors’ varied experiences working and teaching in the field, Analysis of Multivariate Social Science Data, Second Editionenables a basic understanding of how to use key multivariate methods in the social sciences. With updates in every chapter, this edition expands its topics to include regression analysis, confirmatory factor analysis, structural equation models, and multilevel models. After emphasizing the summarization of data in the first several chapters, the authors focus on regression analysis. This chapter provides a link between the two halves of the book, signaling the move from descriptive to inferential methods and from interdependence to dependence. The remainder of the text deals with model-based methods that primarily make inferences about processes that generate data. Relying heavily on numerical examples, the authors provide insight into the purpose and working of the methods as well as the interpretation of data. Many of the same examples are used throughout to illustrate connections between the methods. In most chapters, the authors present suggestions for further work that go beyond conventional exercises, encouraging readers to explore new ground in social science research. Requiring minimal mathematical and statistical knowledge, this book shows how various multivariate methods reveal different aspects of data and thus help answer substantive research questions.

Making Sense of Multivariate Data Analysis

An Intuitive Approach

Author: John Spicer

Publisher: SAGE

ISBN: 9781412904018

Category: Mathematics

Page: 233

View: 1657

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′This book is a helpful guide to reading and understanding multivariate data analysis results in social and psychological research′ _C. Y. Joanne Peng, Indiana University at Bloomington ′This book serves as a resource for readers who want to have an overall view of what encompasses multivariate analyses. The author has discussed some important issues rather philosophically (e.g., theory vs. data analysis). These points are valuable even for readers who have extensive training with multivariate analyses′ _Jenn-Yun Tein, Arizona State University