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Multiple Regression in Practice
Author: William D. Berry, Stanley Feldman
Publisher: SAGE Publications
ISBN: 1544342721
Pages: 96
Year: 1985-05-01
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Berry and Feldman provide a systematic treatment of many of the major problems encountered in using regression analysis. The authors discuss: the consequences of violating the assumptions of the regression model; procedures for detecting when such violations occur; and strategies for dealing with these problems when they arise. The monograph was written without the use of matrix algebra, and numerous examples are provided from political science, sociology, and economics.
Spline Regression Models
Author: Lawrence C. Marsh, David R. Cormier
Publisher: SAGE
ISBN: 0761924205
Pages: 69
Year: 2001-09-14
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Spline Regression Models shows the nuts-and-bolts of using dummy variables to formulate and estimate various spline regression models. For some researchers this will involve situations where the number and location of the spline knots are known in advance, while others will need to determine the number and location of spline knots as part of the estimation process. Through the use of a number of straightforward examples, the authors will show readers how to work with both types of spline knot situations as well as offering practical, down-to-earth information on estimating splines.
Proceedings of the Tenth U.S.-Japan Conference on Composite Materials
Author: Fu-Kuo Chang
Publisher: DEStech Publications, Inc
ISBN: 1932078134
Pages: 1112
Year: 2002-01-01
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Presentations by advanced materials specialists from around the world. Of special interest in this volume are the presentations on application areas such as automotive and civil engineering, nanomaterials, ceramic/metal composites, smart materials, and composite structures.
Master clinicians on treating the regressed patient
Author: Boyer House Foundation
Pages: 394
Year: 1990
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Statistical Learning with Sparsity
Author: Trevor Hastie, Robert Tibshirani, Martin Wainwright
Publisher: CRC Press
ISBN: 1498712177
Pages: 367
Year: 2015-05-07
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Discover New Methods for Dealing with High-Dimensional Data A sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of data. Top experts in this rapidly evolving field, the authors describe the lasso for linear regression and a simple coordinate descent algorithm for its computation. They discuss the application of l1 penalties to generalized linear models and support vector machines, cover generalized penalties such as the elastic net and group lasso, and review numerical methods for optimization. They also present statistical inference methods for fitted (lasso) models, including the bootstrap, Bayesian methods, and recently developed approaches. In addition, the book examines matrix decomposition, sparse multivariate analysis, graphical models, and compressed sensing. It concludes with a survey of theoretical results for the lasso. In this age of big data, the number of features measured on a person or object can be large and might be larger than the number of observations. This book shows how the sparsity assumption allows us to tackle these problems and extract useful and reproducible patterns from big datasets. Data analysts, computer scientists, and theorists will appreciate this thorough and up-to-date treatment of sparse statistical modeling.
Fundamental Statistics for Social Research
Author: Duncan Cramer
Publisher: Psychology Press
ISBN: 0415172047
Pages: 456
Year: 1998-01
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This accessible introduction to statistics using the program SPSS for Windows explains when to apply and how to calculate and interpret a wide range of statistical procedures commonly used in the social sciences. Keeping statistical symbols and formulae to a minimum and using simple examples, this book: * assumes no prior knowledge of statistics or computing * includes a concise introduction to the program SPSS for Windows * describes a wider range of tests than other introductory texts * contains a comprehensive range of exercises with answers Fundamental Statistics for Social Research covers SPSS Release 6 for Windows 3.1 and Release 7 for Windows 95. It will prove an invaluable introductory statistics text for students, and a useful resource for graduates and professionals engaged in research in the social sciences.
Research Design and Statistical Analysis
Author: Jerome L. Myers, Arnold Well
Publisher: Taylor & Francis
Pages: 713
Year: 1995
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This volume provides an extensive treatment of important inferential concepts, experimental designs and related analyses, and regression and correlation analyses. Emphasizing such basic concepts as sampling distributions, expected mean squares, design efficiency, and statistical models, the authors detail the assumptions underlying statistical procedures, the consequences of their violations, methods for detecting those violations, and alternative methods in the face of severe violations. Written for researchers engaged in experimentation and those who conduct observational studies, this volume treats both analysis of variance and regression analysis, and relates the two. And because the assumptions underlying such procedures are often not met by the researcher's data, nonparametric methods are also set forth. Features include: * comprehensive coverage that provides the reader with an understanding of the appropriate statistical analyses for many of the research designs that are likely to be encountered; * emphasis on underlying concepts rather than on computations -- to promote understanding and enable the reader to generalize new applications; * a bottom-up organization that provides concrete examples and intuitive arguments before going into more complex explanations -- to give readers overviews of major topics that encourage understanding; * extensive sets of exercises at the ends of chapters and answers to selected exercises to allow readers to test understanding of concepts as well as the ability to perform calculations; * the development of the basic ideas of multiple regression analysis without using matrix algebra plus an optional section that illustrates the power of the matrix approach -- to make regression analysis accessible to a wide audience; and * discussions of available computer statistical packages, examples of outputs and an appendix about the control information for running the statistical programs -- to help researchers select a computer package and interpret the output.
Perfect Love, Imperfect Relationships
Author: John Welwood
Publisher: Shambhala Publications
ISBN: 083482275X
Pages: 160
Year: 2005-12-27
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While most of us have moments of loving freely and openly, it is often hard to sustain this where it matters most—in our intimate relationships. Why if love is so great and powerful are human relationships so challenging and difficult? If love is the source of happiness and joy, why is it so hard to open to it fully and let it govern our lives? In this book, John Welwood addresses these questions and shows us how to overcome the most fundamental obstacle that keeps us from experiencing love's full flowering in our lives. Perfect Love, Imperfect Relationships begins by showing how all our relational problems arise out of a universal, core wounding around love that affects not only our personal relationships but the quality of life in our world as a whole. This wounding shows up as a pervasive mood of unlove—a deep sense that we are not intrinsically lovable just as we are. And this shuts down our capacity to trust, so that even though we may hunger for love, we have difficulty opening to it and letting it circulate freely through us. This book takes the reader on a powerful journey of healing and transformation that involves learning to embrace our humanness and appreciate the imperfections of our relationships as trail-markers along the path to great love. It sets forth a process for releasing deep-seated grievances we hold against others for not loving us better and against ourselves for not being better loved. And it shows how our longing to be loved can magnetize the great love that will free us from looking to others to find ourselves. Written with penetrating realism and a fresh, lyrical style that honors the subtlety and richness of our relationship to love itself, this revolutionary book offers profound and practical guidance for healing our lives as well as our embattled world.
Practical Guide to Past Life Regression
Author: Florence Wagner McClain
Publisher: Llewellyn Worldwide Limited
Pages: 147
Year: 1986
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Have you ever visited a strange place and felt that you had been there before? Do you struggle with frustrations and fears that seem to have no basis in your present life? Are you afraid of death? This book presents a simple technique that you can use to obtain past life information today. There are no mysterious preparations, no groups to join, no philosophy to which you must adhere. You don't even have to believe in reincarnation. The tools are provided for you to make your own investigations, find your own answers and make your own judgements as to the validity of the information and its usefulness to you.
Linear Models with R, Second Edition
Author: Julian J. Faraway
Publisher: CRC Press
ISBN: 1439887349
Pages: 286
Year: 2016-04-19
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A Hands-On Way to Learning Data Analysis Part of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with R, Second Edition explains how to use linear models in physical science, engineering, social science, and business applications. The book incorporates several improvements that reflect how the world of R has greatly expanded since the publication of the first edition. New to the Second Edition Reorganized material on interpreting linear models, which distinguishes the main applications of prediction and explanation and introduces elementary notions of causality Additional topics, including QR decomposition, splines, additive models, Lasso, multiple imputation, and false discovery rates Extensive use of the ggplot2 graphics package in addition to base graphics Like its widely praised, best-selling predecessor, this edition combines statistics and R to seamlessly give a coherent exposition of the practice of linear modeling. The text offers up-to-date insight on essential data analysis topics, from estimation, inference, and prediction to missing data, factorial models, and block designs. Numerous examples illustrate how to apply the different methods using R.
HBR Guide to Dealing with Conflict (HBR Guide Series)
Author: Amy Gallo
Publisher: Harvard Business Review Press
ISBN: 1633692167
Pages: 192
Year: 2017-03-14
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While some of us enjoy a lively debate with colleagues and others prefer to suppress our feelings over disagreements, we all struggle with conflict at work. Every day we navigate an office full of competing interests, clashing personalities, limited time and resources, and fragile egos. Sure, we share the same overarching goals as our colleagues, but we don't always agree on how to achieve them. We work differently. We rub each other the wrong way. We jockey for position. How can you deal with conflict at work in a way that is both professional and productive—where it improves both your work and your relationships? You start by understanding whether you generally seek or avoid conflict, identifying the most frequent reasons for disagreement, and knowing what approaches work for what scenarios. Then, if you decide to address a particular conflict, you use that information to plan and conduct a productive conversation. The HBR Guide to Dealing with Conflict will give you the advice you need to: Understand the most common sources of conflict Explore your options for addressing a disagreement Recognize whether you—and your counterpart—typically seek or avoid conflict Prepare for and engage in a difficult conversation Manage your and your counterpart's emotions Develop a resolution together Know when to walk away Arm yourself with the advice you need to succeed on the job, with the most trusted brand in business. Packed with how-to essentials from leading experts, the HBR Guides provide smart answers to your most pressing work challenges.
Education, Research and Perspectives
Year: 1998
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Econometrics For Dummies
Author: Roberto Pedace
Publisher: John Wiley & Sons
ISBN: 1118533879
Pages: 360
Year: 2013-06-05
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Score your highest in econometrics? Easy. Econometrics can prove challenging for many students unfamiliar with the terms and concepts discussed in a typical econometrics course. Econometrics For Dummies eliminates that confusion with easy-to-understand explanations of important topics in the study of economics. Econometrics For Dummies breaks down this complex subject and provides you with an easy-to-follow course supplement to further refine your understanding of how econometrics works and how it can be applied in real-world situations. An excellent resource for anyone participating in a college or graduate level econometrics course Provides you with an easy-to-follow introduction to the techniques and applications of econometrics Helps you score high on exam day If you're seeking a degree in economics and looking for a plain-English guide to this often-intimidating course, Econometrics For Dummies has you covered.
Avoiding Regression Effects in Panel Studies of Communication Impact?
Author: Donald T Campbell, Keith N Clayton
Pages: 20
Year: 1961
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Report of National Plans Conference
Year: 1956
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