regression analysis for social sciences

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Regression Analysis For The Social Sciences

Author : Rachel A. Gordon
ISBN : 9781136307744
Genre : Social Science
File Size : 60. 73 MB
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The book provides graduate students in the social sciences with the basic skills that they need to estimate, interpret, present, and publish basic regression models using contemporary standards. Key features of the book include: interweaving the teaching of statistical concepts with examples developed for the course from publicly-available social science data or drawn from the literature. thorough integration of teaching statistical theory with teaching data processing and analysis. teaching of both SAS and Stata "side-by-side" and use of chapter exercises in which students practice programming and interpretation on the same data set and course exercises in which students can choose their own research questions and data set.

Regression Analysis For Social Sciences

Author : Alexander von Eye
ISBN : 9780080550824
Genre : Education
File Size : 81. 92 MB
Format : PDF, ePub
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Regression Analysis for Social Sciences presents methods of regression analysis in an accessible way, with each method having illustrations and examples. A broad spectrum of methods are included: multiple categorical predictors, methods for curvilinear regression, and methods for symmetric regression. This book can be used for courses in regression analysis at the advanced undergraduate and beginning graduate level in the social and behavioral sciences. Most of the techniques are explained step-by-step enabling students and researchers to analyze their own data. Examples include data from the social and behavioral sciences as well as biology, making the book useful for readers with biological and biometrical backgrounds. Sample command and result files for SYSTAT are included in the text. Presents accessible methods of regression analysis Includes a broad spectrum of methods Techniques are explained step-by-step Provides sample command and result files for SYSTAT

Multiple Regression Analysis

Author : Kunal Gaurav
ISBN : 9783656081654
Genre :
File Size : 73. 17 MB
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Seminar paper from the year 2010 in the subject Economics - Statistics and Methods, grade: A, - (All India Management Association, New Dehli, India), course: PhD, language: English, abstract: This is well known fact that the success of social science research heavily depends upon the selection of research tools and its effective utilization. Researchers often come across the situations where they want to study the impact of one variable on the other variable viz. impact of income on expenditure. Although we have freedom to select research tools for multivariate analysis as wide range of research tools are available, multiple regression analysis allows us to determine the effect of more than one independent variable on dependent variable. This term paper talks about the concept of multiple regression analysis, its assumptions, application, and its limitations to the social science research. The paper also briefs about various statistics associated with multiple regression analysis.

Correlation And Regression Analysis

Author : Thomas J. Archdeacon
ISBN : 029913654X
Genre : History
File Size : 31. 78 MB
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In Correlation and Regression Analysis: A Historian's Guide Thomas J. Archdeacon provides historians with a practical introduction to the use of correlation and regression analysis. The book concentrates on the kinds of analysis that form the broad range of statistical methods used in the social sciences. It enables historians to understand and to evaluate critically the quantitative analyses that they are likely to encounter in journal literature and monographs reporting research findings in the social sciences. Without attempting to be a text in basic statistics, the book provides enough background information to allow readers to grasp the essentials of correlation and regression. Correlation analysis refers to the measurement of association between or among variables, and regression analysis focuses primarily on the use of linear models to predict changes in the value taken by one variable in terms of changes in the values of a set of explanatory variables. The book also discusses diagnostic methods for identifying shortcomings in regression models, the use of regression to analyze causation, and the application of regression and related procedures to the study of problems containing categorical as well as numerical data. Archdeacon asserts that knowing how statistical procedures are computed can clarify the theoretical structures underlying them and is essential for recognizing the conditions under which their use is appropriate. The book does not shy away from the mathematics of statistical analysis; but Archdeacon presents concepts carefully and explains the operation of equations step by step. Unlike many works in the field, the book does not assume that readers have mathematical training beyond basic algebra and geometry. In the hope of promoting the role of quantitative analysis in his discipline, Archdeacon discusses the theory and methods behind the most important interpretive paradigm for quantitative research in the social sciences. Correlation and Regression Analysis introduces statistical techniques that are indispensable to historians and enhances the presentation of them with practical examples from scholarly works.

Statistical Analysis In The Social Sciences

Author : McKee J. McClendon
ISBN : 0534637833
Genre : Science
File Size : 81. 91 MB
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Statistical Analysis in the Social Sciences imbeds basic descriptive and inferential statistical concepts within a unified framework: the linear regression model. The regression model is used not only for conducting standard regression analyses but also for other statistical analyses that are ordinarily taught as separate and distinct techniques, such as correlation, difference of means, analysis of variance, and certain nonparametric tests. This extensive use of a single statistical model will increase students' depth of understanding and give them a sense of mastery and self-confidence that they might otherwise fail to achieve in their first statistics course.

Statistics For The Social Sciences

Author : R. Mark Sirkin
ISBN : 141290546X
Genre : Mathematics
File Size : 53. 65 MB
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Popular in previous editions, this Third Edition continues to help build students' confidence and ability in doing statistical analysis by slowly moving from concepts that require little computational work to those that require more. Author R. Mark Sirkin once again demonstrates how statistics can be used so that students come to appreciate their usefulness rather than fear them. Statistics for the Social Sciences emphasizes the analysis and interpretation of data to give students a feel for how data interpretation is related to the methods by which the information was obtained.

Using R For Data Analysis In Social Sciences

Author : Quan Li
ISBN : 9780190656218
Genre : Business & Economics
File Size : 79. 80 MB
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Statistical analysis is common in the social sciences, and among the more popular programs is R. This book provides a foundation for undergraduate and graduate students in the social sciences on how to use R to manage, visualize, and analyze data. The focus is on how to address substantive questions with data analysis and replicate published findings. Using R for Data Analysis in Social Sciences adopts a minimalist approach and covers only the most important functions and skills in R to conduct reproducible research. It emphasizes the practical needs of students using R by showing how to import, inspect, and manage data, understand the logic of statistical inference, visualize data and findings via histograms, boxplots, scatterplots, and diagnostic plots, and analyze data using one-sample t-test, difference-of-means test, covariance, correlation, ordinary least squares (OLS) regression, and model assumption diagnostics. It also demonstrates how to replicate the findings in published journal articles and diagnose model assumption violations. Because the book integrates R programming, the logic and steps of statistical inference, and the process of empirical social scientific research in a highly accessible and structured fashion, it is appropriate for any introductory course on R, data analysis, and empirical social-scientific research.

Applied Regression Analysis And Generalized Linear Models

Author : John Fox
ISBN : 9781483321318
Genre : Social Science
File Size : 77. 97 MB
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Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods, such as bootstrapping and missing data. Updated throughout, this Third Edition includes new chapters on mixed-effects models for hierarchical and longitudinal data. Although the text is largely accessible to readers with a modest background in statistics and mathematics, author John Fox also presents more advanced material in optional sections and chapters throughout the book.

Statistics For Social Sciences With Spss Applications

Author : ASTHANA , HARI SHANKAR
ISBN : 9788120352483
Genre : Social Science
File Size : 22. 14 MB
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Designed as a text for the undergraduate and postgraduate students of psychology, education, sociology, demography and economics, this comprehensive book explains the theoretical and computational aspects of statistics. Since the students of social sciences often find it difficult to comprehend the statistical techniques due to complex mathematical steps involved, this book explains each concept and related statistical derivations or formulae in a simple and clear manner. The text provides solutions to basic concepts and problems using a number of illustrations. In addition, it demonstrates the simplest way of using SPSS software for statistical analysis. SPSS screen images are used to make the ideas more clear to the readers. This is preceded by theoretical details and solved examples so that even those having minimal knowledge of computer can use SPSS easily and comprehend the complex intermediate steps involved in statistical analysis. Besides the undergraduate and postgraduate students of social sciences, the researchers and professionals in this field should find this book immensely useful. The Second Edition of the book has been prepared on the basis of the feedback received from the readers. As per their demand, a new chapter based on multivariate analysis, i.e., Factor analysis has been introduced. Many other chapters have been modified and updated to make them more effective and simple for the readers. Most importantly, screenshots of the latest version of SPSS have been incorporated in the relevant chapters to keep the students abreast with the developments in tools and techniques of statistics.

Applied Logistic Regression Analysis

Author : Scott Menard
ISBN : 0761922083
Genre : Mathematics
File Size : 55. 80 MB
Format : PDF, ePub
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The focus in this Second Editionis on logistic regression models for individual level (but aggregate or grouped) data. Multiple cases for each possible combination of values of the predictors are considered in detail and examples using SAS and SPSS included. New to this edition: · More detailed consideration of grouped as opposed to casewise data throughout the book · Updated discussion of the properties and appropriate use of goodness of fit measures, R2 analogues, and indices of predictive efficiency · Discussion of the misuse of odds ratios to represent risk ratios, and of overdispersion and underdispersion for grouped data · Updated coverage of unordered and ordered polytomous logistic regression models.

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