Research Guides: Computer Programming Library Resources: Social Sciences

Social Sciences: Web Resources

UCLA Stat Consulting Group
Lessons and tutorials on R, Stata, SPSS, and SAS.
Carolina Population Center Data Analysis Tools
Tutorials on Stata and SAS programming.

Social Science Computing: Real World Examples

Social Sciences:

Mason, Winter, Jennifer Wortman Vaughan, and Hanna Wallach. "Computational social science and social computing." Machine Learning 95.3 (2014): 257-60. Online.

Criminology:

Li, Xingan, and Martti Juhola. "Country crime analysis using the self-organizing map, with special regard to demographic factors." AI & SOCIETY 29.1 (2014): 53-68. Online.

Economics:

Manongga, Danny, and M. A. Ineke Pakereng. "Efficiency of Small- and Medium-sized Tofu Enterprises (SME) in Salatiga using Data Envelopment Analysis (DEA)." International Journal of Computer Applications 91.12 (2014). Online.

Education:

Kyriakides, Leonidas, Christiana Christoforou, and Charalambos Y. Charalambous. "What matters for student learning outcomes: A meta-analysis ofstudies exploring factors of effective teaching." Teaching and Teacher Education 36 (2013): 143-52. Online.

History:

Kennedy, Sheridan Wright. "The 1878 Yellow Fever Epidemic in Memphis, Tennessee: An Historical Geographic Information Systems (HGIS) Approach." ProQuest, UMI Dissertations Publishing, 2011.

Spielman, Seth, and Patrick Harrison. "The Co‐evolution of Residential Segregation and the Built Environment at the Turn of the 20th Century: A Schelling Model." Transactions in GIS 18.1 (2014): 25-45. Online.

Politics:

Nickerson, David W., and Todd Rogers. "Political Campaigns and Big Data." Journal of Economic Perspectives 28.2 (2014): 51-74. Online.

Psychology:

Description/Citation.

Sociology:

Romei, Andrea, and Salvatore Ruggieri. "A multidisciplinary survey on discrimination analysis." The Knowledge Engineering Review 29.5 (2014): 582-638. Online.

Computing Resources: Social Sciences

SPSS: Social Sciences Writ Large

Data Mining with SPSS Modeler : Theory, Exercises and Solutions (Second Edition) by Tilo Wendler; Sören Gröttrup
Published: 2021
Introducing the IBM SPSS Modeler, this book guides readers through data mining processesand presents relevant statistical methods. There is a special focus onstep-by-step tutorials and well-documented examples that help demystify complex mathematical algorithms and computer programs. The variety of exercises and solutions as well as an accompanying website with data sets and SPSS Modeler streams are particularly valuable. While intended for students, the simplicity of the Modeler makes the book useful for anyone wishing to learn about basic and more advanced data mining, and put this knowledge into practice. [From the publisher]
Data Analysis with SPSS for Survey-Based Research by Saiyidi Mat Roni and Hadrian Geri Djajadikerta
Published: 2021
This book is written for research students and early-career researchers to quickly and easily learn how to analyse data using SPSS. It follows commonly used logical steps in data analysis design for research. [Publisher]
Using IBM SPSS Statistics for Research Methods and Social Science Statistics by William E. Wagner
Location: HA32 .W34 2013
Published: 2012
Using IBM® SPSS for Social Statistics and Research Methods, Fourth Edition is a useful reference for those learning to use the SPSS software for the first time or those with only basic knowledge about SPSS. [Publisher]
Understanding and Applying Research Design by Martin Lee Abbott; Jennifer McKinney
Location: Available online
Published: 2012
Analyzes real-world data using SPSS software, guiding readers on the overall process of science, focusing on premises, procedures, and designs of social scientific research. .
SPSS for Starters and 2nd Levelers (Second Edition) by Ton J. Cleophas; Aeilko H. Zwinderman
Published: 2015
A complete overview of SPSS methodologies for medical and health statistics. Medical and health professionals tend to dislike software syntax. Therefore, virtually no syntax, but, rather, simple menu commands are given. The arithmetic is...of a no-more-than high-school level. Step-by-step analyses of different statistical methodologies are given with the help of 60 SPSS data files available through the internet. Because of the lack of time of this busy group of people, the authors have given every effort to produce a text as succinct as possible.

SPSS: Psychology

Quantitative and Statistical Research Methods by William E. Martin; Krista D. Bridgmon
Published: 2012
A guide for psychology, counseling, and education students in the use of statistics and research designs, combined with guidance on using SPSS in the course of their research. Each chapter covers a research problem, taking the student through identifying research questions and hypotheses; identifying, classifying, and operationally defining the study variables; choosing appropriate research designs; conducting power analysis; choosing an appropriate statistic for the problem; using a data set; conducting data screening and analyses (SPSS); interpreting the statistics; and writing the results related to the problem.
Explaining Psychological Statistics by Barry H. Cohen
Location: Available online
Published: 2013
Statistics for the non-mathematician, including SPSS screen shots, procedures, exercises, and direction on how to interpret SPSS output.

SPSS: Economics

Exploratory Data Analysis in Business and Economics : An Introduction Using SPSS, Stata, and Excel by Thomas Cleff
Published: 2013
Demonstrates the basic descriptive methods of univariate and bivariate analysis. The textbook covers a range of subject matter, from data collection and scaling to the presentation and univariate analysis of quantitative data, and also includes analytic procedures for assessing bivariate relationships. It does not confine itself to presenting descriptive statistics, but also addresses the use of computer programmes such as Excel, SPSS, and STATA.
A Concise Guide to Market Research by Marko Sarstedt; Erik Mooi
Published: 2018
A hands-on introduction to market research. Using the market research process as a framework, it explains how to collect and describe data and presents the most important and frequently used quantitative analysis techniques, such as ANOVA, regression analysis, factor analysis and cluster analysis. The book describes the theoretical choices a market researcher has to make with regard to each technique, discusses how these are converted into actions in IBM SPSS version 22 and how to interpret the output.

SPSS: Criminal Justice

Statistics in Criminal Justice by David Weisburd; Chester Britt
Published: 2014
This text is meant for both students and researchers who want to gain a basic understanding of common statistical methods used in this field. Throughout the text there is an emphasis on comprehension and interpretation, rather than computation. As the statistical methods discussed become more complex and demanding to compute, there is increasing use and integration of statistical software [including both SPSS and Stata].

Stata: Social Sciences General

The Stata Survival Manual by Pevalin and Robson
An introduction to Stata.

Stata: Economics

Exploratory Data Analysis in Business and Economics : An Introduction Using SPSS, Stata, and Excel by Thomas Cleff
Published: 2013
Demonstrates the basic descriptive methods of univariate and bivariate analysis. The textbook covers a range of subject matter, from data collection and scaling to the presentation and univariate analysis of quantitative data, and also includes analytic procedures for assessing bivariate relationships. It does not confine itself to presenting descriptive statistics, but also addresses the use of computer programmes such as Excel, SPSS, and STATA.
Applied Panel Data Analysis for Economic and Social Surveys by Hans-Jürgen Andreß; Katrin Golsch; Alexander W. Schmidt
Published: 2013
Shows how to manage, describe, and model panel data, presenting models for continuous and categorical dependent variables, focusing either on the level of these variables at different points in time or on their change over time. It covers fixed and random effects models, models for change scores and event history models. All necessary data sets and Stata syntax files on http://eswf.uni-koeln.de/panel

Stata: Criminal Justice

Statistics in Criminal Justice by David Weisburd; Chester Britt
Published: 2014
This text is meant for both students and researchers who want to gain a basic understanding of common statistical methods used in this field. Throughout the text there is an emphasis on comprehension and interpretation, rather than computation. As the statistical methods discussed become more complex and demanding to compute, there is increasing use and integration of statistical software [including both SPSS and Stata].
Statistical Analysis of Management Data by Hubert Gatignon
Published: 2013
A comprehensive approach to multivariate statistical analyses that are important for researchers in all fields of management, including finance, production, accounting, marketing, strategy, technology, and human resources. Examples using STATA are provided for most of the statistical methods. The book may serve as an advanced text or as a resource for applied researchers in industry who want to understand the foundations of the methods particularly relevant and typically used in management research, and to learn how they can be applied using widely available statistical software.

Stata: Behavioral and Social Sciences

Multivariate Analysis for the Biobehavioral and Social Sciences by Bruce L. Brown; Dawson W. Hedges; Suzanne B. Hendrix; Timothy B. Smith
Published: 2011
Guide to understanding and visualizing multivariate statistics using SAS®, STATA®, and SPSS®. The book begins with a preparatory review of univariate statistical methods recast in matrix notation, followed by an accessible introduction to matrix algebra. Subsequent chapters explore fundamental multivariate methods and related key concepts, including: Factor analysis and related methods, Multivariate graphics, Canonical correlation, Hotelling's T-squared, Multivariate analysis of variance (MANOVA), and Multiple regression and the general linear model (GLM).

R for SAS and SPSS Users by Robert A. Muenchen
Published: 2011
This book introduces R using SAS and SPSS terms with which you are already familiar. It demonstrates which of the add-on packages are most like SAS and SPSS and compares them to R's built-in functions. It steps through over 30 programs written in all three packages, comparing and contrasting the packages' differing approaches. The programs and practice datasets are available for download. When finished, you will be able to import data, manage and transform it, create publication quality graphics, and perform basic statistical analyses.
Introduction to Data Science to Social and Policy Research: Collecting and Organizing Data with R and Python by Jose Manuel Magallanes Reyes
Location: Available online
Published: 2017
Qualitative comparative analysis using R : a beginner's guide by Ioana-Elena Oana, Carsten Q. Schneider, Eva Thomann
Published: 2021
A comprehensive introduction and teaching resource for state-of-the-art Qualitative Comparative Analysis (QCA) using R software. [Publisher]
Qualitative Comparative Analysis with R by Alrik Thiem and Adrian Dusa
Published: 2013
Offers the first complete introduction on how to perform Qualitative Comparative Analysis (QCA) in the R software environment for statistical computing and graphics with the QCA package. QCA provides an unprecedented scope of functionality for analyzing crisp, multi-value and fuzzy sets. The reader is not required to have knowledge of R, but the book assumes an understanding of the fundamentals of QCA. Although mainly written for political scientists, this book is also of interest to scholars from other disciplines in the social sciences such as sociology, business, management, organization, anthropology, education and health.
R for Stata Users by Robert A. Muenchen; Joseph M. Hilbe
Published: 2010
Introduces R using Stata terminology. When finished, you will be able to use R in conjunction with Stata, or separately, to import data, manage and transform it, create publication quality graphics, and perform basic statistical analyses. A glossary defines over 50 R terms using Stata jargon and again using more formal R terminology. The table of contents and index allow you to find equivalent R functions by looking up Stata commands and vice versa. The example programs and practice datasets for both R and Stata are available for download.
Data Manipulation with R by Phil Spector
Published: 2008
Introduces the structure of data in R, along with subscripting, character manipulation, reshaping data, and other data manipulation basics. Great for understanding the mechanics of R, which may not be explained in statistics texts.
Introductory Statistics with R by Peter Dalgaard
Published: 2008
An elementary-level introduction to R. A supplementary R package can be downloaded and contains the data sets. The statistical methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one-and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last four chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis.

R: Behavioral Research

Behavioral Research Data Analysis with R by Yuelin Li; Jonathan Baron
Published: 2011
This book is written for behavioral scientists who want to consider adding R to their existing set of statistical tools, or want to switch to R as their main computation tool. The authors aim primarily to help practitioners of behavioral research make the transition to R. The focus is to provide practical advice on some of the widely-used statistical methods in behavioral research, using a set of notes and annotated examples.

R: Economics and Business

R for Business Analytics by A. Ohri
Published: 2013
Looks at some of the most common tasks performed by business analysts and helps the user navigate R and its 4000 packages. Includes chapters on data visualization, code examples on web analytics and social media analytics, clustering, regression models, text mining, data mining models and forecasting. This book is aimed at business analysts with basic programming skills for using R for Business Analytics. Business analytics (BA) refers to the field of exploration and investigation of data generated by businesses (i.e. models to predict and strategize and DM matches patterns in big data).
Statistical Analysis of Financial Data in R by René Carmona
Published: 2013
Intended for undergraduate students majoring in financial engineering, or graduate students in a Master in finance or MBA program. Practical examples are solved in the R computing environment, illustrating proglems occurring in the commodity, energy and weather markets, as well as the fixed income, equity and credit markets.
Time Series Analysis and Its Applications (4th ed.) by Robert H. Shumway; David S. Stoffer
ISBN: 9783319524528
Published: 2017
In addition to coverage of classical methods of time series regression, ARIMA models, spectral analysis and state-space models, the text includes modern developments including categorical time series analysis, multivariate spectral methods, long memory series, nonlinear models, resampling techniques, GARCH models, stochastic volatility, wavelets and Monte Carlo Markov chain integration methods.

R: Politics

Political Analysis with R by James E. Monogan III
Published: 2015

Forensic GIS by Gregory Elmes (Editor); George Roedl (Editor); Jamison Conley (Editor)
Published: 2014
A variety of disciplines and professions have embraced geospatial technologies for collecting, storing, manipulating, analyzing and displaying spatial data to investigate crime, prosecute and convict offenders, exonerate suspects and submit evidence in civil lawsuits. The applications, acceptability and relevance and procedural legality of each geospatial technologies vary. The purpose of this book is to explain the nature of geospatial technologies, demonstrate a variety of geospatial applications used to investigate and litigate civil and criminal activities and to provide a reference of current acceptability of geospatial technology in the production of evidence. This book is an introductory overview designed to appeal to researchers and practitioners across disciplinary boundaries. The authors of this book are researchers and practitioners across disciplines and professions, experts in the field.
Spatial Econometrics by Harry Kelejian; Gianfranco Piras
Location: HB139 .K446 2017
ISBN: 9780128133873
Published: 2017
Subjects covered at length include spatial regression models, weighting matrices, estimation procedures and the complications associated with their use. The work particularly focuses on models of uncertainty and estimation under various complications relating to model specifications, data problems, tests of hypotheses, along with systems and panel data extensions which are covered in exhaustive detail. [Publisher]
Spatial Analysis and Modeling in Geographical Transformation Process by Yuji Murayama (Editor); Rajesh Bahadur Thapa (Editor)
Published: 2011
This book deals with spatial analysis and modelling. It provides a comprehensive discussion of spatial analysis, methods, and approaches related to human settlements and associated environment. Key contributions with empirical case studies from Iran, Philippines, Vietnam, Thailand, Nepal, and Japan...It provides a milestone reference to students, researchers, planners, and other practitioners dealing the spatial problems on urban and regional issues.