Basic Math for Social Scientists

Author: Timothy Hagle
Publisher: SAGE
ISBN: 9780803958753
Format: PDF, Mobi
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A review of the basic mathematical concepts that underlie most quantitative analysis in the social sciences is presented in this volume. The author begins with an algebra review featuring sets and combinations and then discusses limits and continuity. Calculus is presented next, with an introduction to differential calculus, multivariate functions, partial derivatives, and integral calculus. Finally the book deals with matrix algebra. Packed with helpful definitions, equations, examples and alternative notations, the book also includes a useful appendix of common mathematical symbols and Greek letters.

A Mathematical Primer for Social Statistics

Author: John Fox
Publisher: SAGE
ISBN: 1412960800
Format: PDF
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Beyond the introductory level, learning and effectively using statistical methods in the social sciences requires some knowledge of mathematics. This handy volume introduces the areas of mathematics that are most important to applied social statistics.

Mathematics for Social Scientists

Author: Jonathan Kropko
Publisher: SAGE Publications
ISBN: 1506304222
Format: PDF, Kindle
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Written for social science students who will be working with or conducting research, Mathematics for Social Scientists offers a non-intimidating approach to learning or reviewing math skills essential in quantitative research methods. The text is designed to build students’ confidence by presenting material in a conversational tone and using a wealth of clear and applied examples. Author Jonathan Kropko argues that mastering these concepts will break students’ reliance on using basic models in statistical software, allowing them to engage with research data beyond simple software calculations.

Basic Math for Social Scientists

Author: Timothy Hagle
Publisher: SAGE Publications
ISBN: 1506317707
Format: PDF, Mobi
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This book of worked-out examples not only accompanies Timothy M. Hagle's earlier book Basic Math for Social Scientists: Concepts, but also provides an informal refresher course in algebra sets, limits and continuity, differential calculus, multivariate functions, partial derivatives, integral calculus, and matrix algebra. Problem sets are also provided so that readers can practice their grasp of standard mathematical procedures.

Calculus

Author: Gudmund R. Iversen
Publisher: SAGE
ISBN: 9780803971103
Format: PDF, ePub
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This book offers an overview of the central ideas in calculus and gives examples of how calculus is used to translate many real-world phenomena into mathematical functions. Beginning with an explanation of the two major parts of calculus - differentiation and integration - Gudmund R Iversen illustrates how calculus is used in statistics: to distinguish between the mean and the median; to derive the least squares formulas for regression co-efficients; to find values of parameters from theoretical distributions; and to find a statistical p-value when using one of the continuous test variables such as the t-variable.

The Logic of Causal Order

Author: James A. Davis
Publisher: SAGE
ISBN: 9780803925533
Format: PDF, ePub, Mobi
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This monograph is not statistical. It looks instead at pre-statistical assumptions about dependent variables and causal order. Professor Davis spells out the logical principles that underlie our ideas of causality and explains how to discover causal direction, irrespective of the statistical technique used. He stresses throughout that knowledge of the "real world" is important and repeatedly challenges the myth that causal problems can be solved by statistical calculations alone.

Differential Equations

Author: Courtney Brown
Publisher: SAGE
ISBN: 9781412941082
Format: PDF, Docs
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Differential Equations: A Modeling Approach introduces differential equations and differential equation modeling to students and researchers in the social sciences. Key Features: - The text is accessibly written, so that students with minimal mathematical training can understand all of the basic concepts and techniques presented. - The author uses social sciences examples to illustrate the relevance of differential equation modeling to readers. - Readers can use graphical methods to produce penetrating analysis of differential equation systems. - Linear and nonlinear model specifications are explained from a social science perspective. Most interesting differential equation models are nonlinear, and readers need to know how to specify and work with such models in the social sciences.

Basic Content Analysis

Author: Robert Philip Weber
Publisher: SAGE
ISBN: 9780803938632
Format: PDF, ePub
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This second edition of Basic Content Analysis is completely updated and offers a concise introduction to content analysis methods from a social science perspective. It includes new computer applications, new studies and an additional chapter on problems and issues that can arise when carrying out content analysis in four major areas: measurement, indication, representation and interpretation.

Game Theory

Author: Frank C. Zagare
Publisher: SAGE
ISBN: 9780803920507
Format: PDF, Docs
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The concepts of game theory (rationality etc) now pervade much of social science, so that Professor Zagare's exposition of game theory and its applications (intended to "convert the unconverted and initiate the uninitiated") is very welcome. He provides methods for analysing the structure of the game; considers zero and nonzero-sum games and the fundamental 'minimax theorem'; and investigates games with more than two players, including the possibility of coalitions between players. Diverse examples give the reader an idea of how the theory can be applied to a wide range of situations.

Bootstrapping

Author: Christopher Z. Mooney
Publisher: SAGE
ISBN: 9780803953819
Format: PDF, ePub
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Bootstrapping, a computational nonparametric technique for "re-sampling," enables researchers to draw a conclusion about the characteristics of a population strictly from the existing sample rather than by making parametric assumptions about the estimator. Using real data examples from per capita personal income to median preference differences between legislative committee members and the entire legislature, Mooney and Duval discuss how to apply bootstrapping when the underlying sampling distribution of the statistics cannot be assumed normal, as well as when the sampling distribution has no analytic solution. In addition, they show the advantages and limitations of four bootstrap confidence interval methods: normal approximation, percenti