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Applied Regression

Author: Michael S. Lewis-Beck
Publisher: SAGE
ISBN: 9780803914940
Size: 49.62 MB
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Applied regression allows social scientists who are not specialists in quantitative techniques to arrive at clear verbal explanations of their numerical results. Provides a lucid discussion of more specialized subjects: analysis of residuals, interaction effects, specification error, multicollinearity, standardized coefficients, and dummy variables.

Applied Regression

Author: Colin Lewis-Beck
Publisher: SAGE Publications
ISBN: 1483381498
Size: 33.33 MB
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Known for its readability and clarity, this Second Edition of the best-selling Applied Regression provides an accessible introduction to regression analysis for social scientists and other professionals who want to model quantitative data. After covering the basic idea of fitting a straight line to a scatter of data points, the text uses clear language to explain both the mathematics and assumptions behind the simple linear regression model. Authors Colin Lewis-Beck and Michael Lewis-Beck then cover more specialized subjects of regression analysis, such as multiple regression, measures of model fit, analysis of residuals, interaction effects, multicollinearity, and prediction. Throughout the text, graphical and applied examples help explain and demonstrate the power and broad applicability of regression analysis for answering scientific questions.

Applied Regression

Author: Michael Lewis-Beck
Publisher: SAGE Publications
ISBN: 1452208093
Size: 17.77 MB
Format: PDF, Kindle
View: 1051
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Applied regression allows social scientists who are not specialists in quantitative techniques to arrive at clear verbal explanations of their numerical results. Provides a lucid discussion of more specialized subjects: analysis of residuals, interaction effects, specification error, multicollinearity, standardized coefficients, and dummy variables.

Data Analysis

Author: Michael Lewis-Beck
Publisher: SAGE
ISBN: 9780803957725
Size: 59.41 MB
Format: PDF, Mobi
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This accessible introduction to data analysis focuses on the interpretation of statistical results, in particular those which come from nonexperimental social research. It will provide social science researchers with the tools necessary to select and evaluate statistical tests appropriate for their research question. Using a consistent data-set throughout the book to illustrate the various analytic techniques, Michael Lewis-Beck covers topics such as univariate statistics, measures of association, the statistical significance of the relationship between two variables, simple regression in which the dependent variable is influenced by a single independent variable, and multiple regression.

Regression Diagnostics

Author: John Fox
Publisher: SAGE
ISBN: 9780803939714
Size: 42.94 MB
Format: PDF, ePub
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With Regression Diagnostics, researchers now have an accessible explanation of the techniques needed for exploring problems that compromise a regression analysis and for determining whether certain assumptions appear reasonable. The book covers such topics as the problem of collinearity in multiple regression, dealing with outlying and influential data, non-normality of errors, non-constant error variance and the problems and opportunities presented by discrete data. In addition, sophisticated diagnostics based on maximum-likelihood methods, scores tests, and constructed variables are introduced.

Modern Methods For Robust Regression

Author: Robert Andersen
Publisher: SAGE
ISBN: 1412940729
Size: 34.51 MB
Format: PDF, Docs
View: 1943
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Geared towards both future and practising social scientists, this book takes an applied approach and offers readers empirical examples to illustrate key concepts. It includes: applied coverage of a topic that has traditionally been discussed from a theoretical standpoint; empirical examples to illustrate key concepts; a web appendix that provides readers with the data and the R-code for the examples used in the book.

The Sage Encyclopedia Of Social Science Research Methods

Author: Michael Lewis-Beck
Publisher: SAGE
ISBN: 9780761923633
Size: 39.28 MB
Format: PDF, Mobi
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"The first encyclopedia to cover inclusively both quantitative and qualitative research approaches, this set provides clear explanations of 1,000 methodologies, avoiding mathematical equations when possible with liberal cross-referencing and bibliographies. Each volume includes a list of works cited, and the third contains a comprehensive index and lists of person names, organizations, books, tests, software, major concepts, surveys, and methodologies."--"Reference that rocks," American Libraries, May 2005.

Digital Analytics Primer

Author: Judah Phillips
Publisher: FT Press
ISBN: 0133552101
Size: 23.22 MB
Format: PDF
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Learn the concepts and methods for creating economic and business value with digital analytics, mobile analytics, web analytics, and market research and social media data. In Digital Analytics Primer , pioneering expert Judah Phillips introduces the concepts, terms, and methods that comprise the science and art of digital analysis for web, site, social, video, and other types of quantitative and qualitative data. Business readers—from new practitioners to experienced executives—who want to understand how digital analytics can be used to reduce costs and increase profitable revenue throughout the business should read this book. Phillips delivers a comprehensive review of the core concepts, vocabulary, and frameworks, including analytical methods and tools that can help you successfully integrate analytical processes, technology, and people into all aspects of business operations. This unbiased and product-independent primer draws from the author's extensive experience doing and managing analytics in this field.

Applied Logistic Regression Analysis

Author: Scott W. Menard
Publisher: Sage Publications, Inc
ISBN:
Size: 19.64 MB
Format: PDF, Kindle
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Emphasizing the parallels between linear and logistic regression, Scott Menard explores logistic regression analysis and demonstrates its usefulness in analyzing dichotomous, polytomous nominal, and polytomous ordinal dependent variables. The book is aimed at readers with a background in bivariate and multiple linear regression.