Basic Math for Social Scientists

Author: Timothy Hagle
Publisher: SAGE
ISBN: 0803972857
Release Date: 1996-03-01
Genre: Mathematics

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.

A Mathematical Primer for Social Statistics

Author: John Fox
Publisher: SAGE
ISBN: 9781412960809
Release Date: 2009
Genre: Mathematics

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: 9781506304229
Release Date: 2015-09-09
Genre: Social Science

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.

Bootstrapping

Author: Christopher Z. Mooney
Publisher: SAGE
ISBN: 080395381X
Release Date: 1993-08-09
Genre: Social Science

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

Basic Content Analysis

Author: Robert Philip Weber
Publisher: SAGE
ISBN: 0803938632
Release Date: 1990
Genre: Language Arts & Disciplines

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.

Experimental Design and Analysis

Author: Steven R. Brown
Publisher: SAGE
ISBN: 0803938543
Release Date: 1990
Genre: Mathematics

This volume introduces the reader to one of the most fundamental topics in social science statistics: experimental design. The authors clearly show how to select an experimental design based on the number of independent variables and the number of subjects. Other topics addressed include variability, hypothesis testing, how ANOVA can be extended to the multi-group situation, the logic of the t test and completely randomized designs.

Translating Questionnaires and Other Research Instruments

Author: Orlando Behling
Publisher: SAGE
ISBN: 0761918248
Release Date: 2000-05-24
Genre: Reference

This book covers the essential information needed to understand the problems involved in translating existing questionnaires and other paper and pencil instruments from one language to another as well as to apply methods for dealing with them. It shows researchers how to identify the problems (comparison of parameters, nomological nets, and semantic problems) with an existing instrument; how to solve each of these problems with step-by-step guidelines; and techniques for reconstructing an instrument or designing an original one to use with different cultural groups. This book will provide researchers with a guide for construction of cross-national survey instruments.

Introduction to Applied Bayesian Statistics and Estimation for Social Scientists

Author: Scott M. Lynch
Publisher: Springer Science & Business Media
ISBN: 9780387712659
Release Date: 2007-06-30
Genre: Social Science

This book outlines Bayesian statistical analysis in great detail, from the development of a model through the process of making statistical inference. The key feature of this book is that it covers models that are most commonly used in social science research - including the linear regression model, generalized linear models, hierarchical models, and multivariate regression models - and it thoroughly develops each real-data example in painstaking detail.

Statistics for the Social Sciences

Author: R. Mark Sirkin
Publisher: SAGE
ISBN: 141290546X
Release Date: 2006
Genre: Mathematics

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.

Matrix Algebra An Introduction

Author: Krishnan Namboodiri
Publisher: Sage Publications (CA)
ISBN: 148334729X
Release Date: 1984-07-01
Genre: Mathematics

Matrix Algebra is a vital tool for mathematics in the social sciences, and yet many social scientists have only a rudimentary grasp of it. This volume serves as a complete introduction to matrix algebra, requiring no background knowledge beyond basic school algebra. Namboodiri's presentation is smooth and readable: it begins with the basic definitions and goes on to explain elementary manipulations and the concept of linear dependence, eigenvalues, and eigenvectors -- supplying illustrations through fully-worked examples.

LISREL Approaches to Interaction Effects in Multiple Regression

Author: James Jaccard
Publisher: SAGE
ISBN: 0803971796
Release Date: 1996-03-21
Genre: Social Science

With detailed examples, this book demonstrates the use of the computer program LISREL and how it can be applied to the analysis of interactions in regression frameworks. The authors consider a wide range of applications including: qualitative moderator variables; longitudinal designs; and product term analysis. They describe different types of measurement error and then present a discussion of latent variable representations of measurement error which serves as the foundation for the analyses described in later chapters. Finally they offer a brief introduction to LISREL and show how it can be used to execute the analyses. Readers can use this book without any prior training in LISREL and will find it an excellent introduction to analytic methods that deal with the problem of measurement error in the analysis of interactions.

A Mathematics Course for Political and Social Research

Author: Will H. Moore
Publisher: Princeton University Press
ISBN: 9781400848614
Release Date: 2013-07-24
Genre: Political Science

Political science and sociology increasingly rely on mathematical modeling and sophisticated data analysis, and many graduate programs in these fields now require students to take a "math camp" or a semester-long or yearlong course to acquire the necessary skills. Available textbooks are written for mathematics or economics majors, and fail to convey to students of political science and sociology the reasons for learning often-abstract mathematical concepts. A Mathematics Course for Political and Social Research fills this gap, providing both a primer for math novices in the social sciences and a handy reference for seasoned researchers. The book begins with the fundamental building blocks of mathematics and basic algebra, then goes on to cover essential subjects such as calculus in one and more than one variable, including optimization, constrained optimization, and implicit functions; linear algebra, including Markov chains and eigenvectors; and probability. It describes the intermediate steps most other textbooks leave out, features numerous exercises throughout, and grounds all concepts by illustrating their use and importance in political science and sociology. Uniquely designed and ideal for students and researchers in political science and sociology Uses practical examples from political science and sociology Features "Why Do I Care?" sections that explain why concepts are useful Includes numerous exercises Complete online solutions manual (available only to professors, email david.siegel at duke.edu, subject line "Solution Set") Selected solutions available online to students

The SAGE Handbook of Quantitative Methodology for the Social Sciences

Author: David Kaplan
Publisher: SAGE Publications
ISBN: 9781483365879
Release Date: 2004-06-21
Genre: Social Science

The SAGE Handbook of Quantitative Methodology for the Social Sciences is the definitive reference for teachers, students, and researchers of quantitative methods in the social sciences, as it provides a comprehensive overview of the major techniques used in the field. The contributors, top methodologists and researchers, have written about their areas of expertise in ways that convey the utility of their respective techniques, but, where appropriate, they also offer a fair critique of these techniques. Relevance to real-world problems in the social sciences is an essential ingredient of each chapter and makes this an invaluable resource.

Quantitative Social Science

Author: Kosuke Imai
Publisher: Princeton University Press
ISBN: 9781400885251
Release Date: 2017-02-27
Genre: Social Science

Quantitative analysis is an increasingly essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it—or if they do, they usually end up in statistics classes that offer few insights into their field. This textbook is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, such as economics, sociology, public policy, and data science. Quantitative Social Science engages directly with empirical analysis, showing students how to analyze data using the R programming language and to interpret the results—it encourages hands-on learning, not paper-and-pencil statistics. More than forty data sets taken directly from leading quantitative social science research illustrate how data analysis can be used to answer important questions about society and human behavior. Proven in the classroom, this one-of-a-kind textbook features numerous additional data analysis exercises and interactive R programming exercises, and also comes with supplementary teaching materials for instructors. Written especially for students in the social sciences and allied fields, including economics, sociology, public policy, and data science Provides hands-on instruction using R programming, not paper-and-pencil statistics Includes more than forty data sets from actual research for students to test their skills on Covers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical tools Features a wealth of supplementary exercises, including additional data analysis exercises and interactive programming exercises Offers a solid foundation for further study Comes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides