Basic Math for Social Scientists

In his first volume , Basic Math for Social Scientists : Concepts ( No. 108 ) , Dr. Hagle explained fundamental mathematics concepts behind data analysis techniques . In this second volume , he returns to the same concepts ...

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Author: Timothy Hagle

Publisher: SAGE

ISBN: 0803972857

Category: Mathematics

Page: 102

View: 682

This book of worked-out examples provides an informal refresher course in algebra sets, limits and continuity, differential calculus, integral calculus, multivariate functions and partial derivatives.

Basic Math for Social Scientists

Aimed at readers who have taken one or two courses in algebra, this volume is packed with helpful definitions, equations, and examples as well as alternative notations.

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Author: Timothy M. Hagle

Publisher:

ISBN: 1544307772

Category: Mathematics

Page: 96

View: 420

Taking an informal approach, Hagle presents a review of the basic mathematical concepts that underlie most quantitative analysis in the social sciences. After an algebra review featuring sets and combinations, Hagle discusses limits and continuity. Calculus is presented next, with an introduction to differential calculus. Multivariate functions, partial derivatives and integral calculus are discussed; the author concludes with a discussion of matrix algebra. Aimed at readers who have taken one or two courses in algebra, this volume is packed with helpful definitions, equations, and examples as well as alternative notations. A useful appendix of common math symbol and Greek letters is also included. Learn more about "The Little Green Book"--QASS Series!

Basic Math for Social Scientists

Aimed at readers who have taken one or two courses in algebra, this volume is packed with helpful definitions, equations, and examples as well as alternative notations.

DOWNLOAD NOW »

Author: Timothy Hagle

Publisher: SAGE

ISBN: 0803958757

Category: Mathematics

Page: 96

View: 119

Taking an informal approach, Hagle presents a review of the basic mathematical concepts that underlie most quantitative analysis in the social sciences. After an algebra review featuring sets and combinations, Hagle discusses limits and continuity. Calculus is presented next, with an introduction to differential calculus. Multivariate functions, partial derivatives and integral calculus are discussed; the author concludes with a discussion of matrix algebra. Aimed at readers who have taken one or two courses in algebra, this volume is packed with helpful definitions, equations, and examples as well as alternative notations. A useful appendix of common math symbol and Greek letters is also included. Learn more about "The Little Green Book"--QASS Series!

A Mathematical Primer for Social Statistics

Typical introductory statistics courses taught to social science students use onlyverybasic mathematicsarithmetic, simple formulas, the abilityto interpretagraph.Therearegoodreasonsforthis:Mostsocialsciencestudents have weak ...

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Author: John Fox

Publisher: SAGE

ISBN: 9781412960809

Category: Mathematics

Page: 170

View: 375

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

One thing that math is not is easy. Math can be very challenging, ... Given the stigma of math, it's not surprising that many new social science graduate students haven't had a math class since high school. The amount of math needed to ...

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Author: Jonathan Kropko

Publisher: SAGE Publications

ISBN: 9781506304236

Category: Social Science

Page: 408

View: 503

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. Available with Perusall—an eBook that makes it easier to prepare for class Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.

Basic Content Analysis

Quantitative Applications in the Social Sciences A SAGE UNIVERSITY PAPERS SERIES SAGE PUBLICATIONS International Educational and Professional Publisher Thousand ... Basic Math for Social Scientists : Problems and Solutions Hagle 110.

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Author: Robert Philip Weber

Publisher: SAGE

ISBN: 0803938632

Category: Social Science

Page: 96

View: 943

This second edition has been completely updated to include new studies, new computer applications and an additional chapter on problems and issues that can arise when carrying out content analysis in four major categories: measurement, indication, representation and interpretation.

Summated Rating Scale Construction

Quantitative Applications in the Social Sciences A SAGE UNIVERSITY PAPERS SERIES SAGE PUBLICATIONS International Educational and Professional Publisher Thousand ... Basic Math for Social Scientists : Problems and Solutions Hagle 110.

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Author: Paul E. Spector

Publisher: SAGE

ISBN: 0803943415

Category: Psychology

Page: 72

View: 720

Intended for the social scientist who must develop a rating on attitudes, values and opinions, this text provides information on the construction of more effective scales. It includes information on how to validate a scale and how to develop a summated rating scale based on classical test theory.

Introduction to Applied Bayesian Statistics and Estimation for Social Scientists

Bayesian Methods: A Social and Behavioral Sciences Approach. Boca Raton, FL: Chapman & Hall/CRC. Hagle, T.M. (1996) Basic Math for Social Scientists: Problems and Solutions. Sage University Paper Series on Quantitative Applications in ...

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Author: Scott M. Lynch

Publisher: Springer Science & Business Media

ISBN: 9780387712659

Category: Social Science

Page: 359

View: 118

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.

Social Network Analysis

Sciences. A. SAGE. PUBLICATIONS. SERIES. Series/Number 07–154 SOCIAL NETWORK ANALYSIS 2nd Edition David Knoke University ... Nonparametric Simple Regression: 96. Maximum Likelihood Estimation ... Basic Math for Social Scientists: 142.

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Author: David Knoke

Publisher: SAGE

ISBN: 9781412927499

Category: Social Science

Page: 132

View: 946

Providing a general overview of fundamental theoretical and methodological topics, with coverage in greater depth of selected issues, the text covers various issues in basic network concepts, data collection and network analytical methodology.

Multidimensional Scaling

Quantitative Applications in the Social Sciences A SAGE UNIVERSITY PAPERS SERIES SAGE PUBLICATIONS International Educational and Professional Publisher Thousand ... Basic Math for Social Scientists : Problems and Solutions Hagle 110.

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Author: Joseph B. Kruskal

Publisher: SAGE

ISBN: 0803909403

Category: Social Science

Page: 93

View: 292

Outlines a set of techniques that enable a researcher to discuss the "hidden structure" of large data bases. These techniques use proximities, measures which indicate how similar or different objects are, to find a configuration of points which reflects the structure in the data.