This book provides an introduction to data science that is tailored to the needs of students in psychology, but is also suitable for students of the humanities and other biological or social sciences. This audience typically has some knowledge of statistics, but rarely an idea how data is prepared for statistical testing. By using various data types and working with many examples, we teach strategies and tools for reshaping, summarizing, and visualizing data. By keeping our eyes open for the perils of misleading representations, the book fosters fundamental skills of data literacy and cultivates reproducible research practices that enable and precede any practical use of statistics. Read more →

Are you interested in learning R, but intimidated by programming and statistical analysis? ‘R for Non-Programmers: A Guide for Social Scientists’ is the perfect resource for you. This book provides practical and efficient solutions to common challenges in empirical research in the Social Sciences, without assuming any prior knowledge or skills in programming or statistical analysis. Each chapter is dedicated to a specific task required to answer research questions and includes exercises and case studies based on real data. Whether you are a novice or experienced analyst, this book is a comprehensive entry to R programming that will help enhance your data analysis skills. Read more →

A book created with bookdown. […] Suggested citation: Ziller, Conrad (2024). Introduction to Statistics and Data Analysis – A Case-Based Approach. Available online at https://bookdown.org/conradziller/introstatistics To download the R-Scripts and data used in this book, go HERE. A PDF-version of the book can be downloaded HERE. This short book is a complete introduction to statistics and data analysis using R and RStudio. It contains hands-on exercises with real data—mostly from social sciences. In addition, this book presents four key ingredients of statistical data analysis (univariate … Read more →

Felix Lennert Dear student, if you read this script, you are either participating in one of my courses on digital methods for the social sciences, or at least interested in this topic. If you have any questions or remarks regarding this script, hit me up at felix.lennert@ensae.fr. This script will introduce you to two techniques I regard as elementary for any aspiring (computational) social scientist: the collection of digital trace data via either scraping the web or acquiring data from application programming interfaces (APIs) and the analysis of text in an automated fashion (text mining). … Read more →

Felix Lennert Dear student, if you read this script, you are either participating in one of my courses on digital methods for the social sciences, or at least interested in this topic. If you have any questions or remarks regarding this script, hit me up at felix.lennert@ensae.fr. This script will introduce you to two techniques I regard as elementary for any aspiring (computational) social scientist: the collection of digital trace data via either scraping the web or acquiring data from application programming interfaces (APIs) and the analysis of text in an automated fashion (text mining). … Read more →

This is a minimal example of using the bookdown package to write a book. The HTML output format for this example is bookdown::gitbook, set in the _output.yml file. [...] This book is a repository of my notes in computational social science from reading Salganik’s Bit By Bit, as well as open access curricula released by the SICSS ... Read more →

This will serve as a course reader for SOC 128D, Summer 2023. […] Office Hours: Fridays and Mondays, 11:00am-12:30pm https://calendly.com/tylermcdaniel/tyler-s-office-hours Course Description: Data science has rapidly gained recognition within the social sciences because it offers powerful new ways to ask questions about social systems and problems. This course will examine how tools from data science can be used to analyze pressing issues relating to disaster, inequality, and scarcity in the Anthropocene (the current period in which humans are the primary driver of planetary changes). We … Read more →

This book is supposed to introduce the reader (i.e., you) to a fundamental technique for computational social science research: the quantitative analysis of text. […] Dear student, if you read this script, you are either participating in one of my courses on digital methods for the social sciences, or at least interested in this topic. If you have any questions or remarks regarding this script, hit me up at felix.lennert@ensae.fr. This script will introduce you to the quantitative analysis of text using R. Through the last decades, more and more text has become readily available. Think for … Read more →

This book serves as an accompanying script for the R sessions of the 2023 Summer Institute for Computational Social Science (SICSS), taking place at the Institut Polytechnique de Paris. […] Dear student, if you read this script, you are either participating in the SICSS itself or came across it while browsing for resources for your studies. In any case, if you find inconsistencies or mistakes, please do not hesitate to point them out by shooting an email to felix.lennert@ensae.fr. This script will introduce you to the automated acquisition and subsequent quantitative analysis of text data … Read more →

This book provides basic material for students seeking to learn statistics in an R environment, […] This skills pack introduces statistical concepts to beginners within the framework of R. Examples of analyses and R code are provided as well. Dr. Glenna Nightingale PhD Statistics research scientist (public health, epidemiology, spatial ecology, computational social science). Dr. Mike Allerhand, PhD Statistics -since 2009 Statistician at the Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh. Since 2018 Statistical Consultant in the Statistical Consultancy Unit … Read more →

This ebook is an effort to connect Hayes’s conditional process analysis work with the Bayesian paradigm. Herein I refit his models with my favorite R package for Bayesian regression, Bürkner’s brms, and use the tidyverse for data manipulation and plotting. […] Andrew Hayes’s (2018) text, Introduction to mediation, moderation, and conditional process analysis: A regression-based approach, has become a staple in social science graduate education. Hayes’s work has been from a frequentist OLS perspective. This book is an effort to connect his work with the Bayesian paradigm. Herein I refit his … Read more →

This book is supposed to introduce the reader (i.e., you) into some fundamental techniques for computational social science research: acquiring online data, agent-based modeling, and text mining. […] Dear student, if you read this script, you are either participating in one of my courses on digital methods for the social sciences, or at least interested in this topic. If you have any questions or remarks regarding this script, hit me up at felix.lennert@ensae.fr. This script will introduce you to three techniques I regard as elementary for any aspiring (computational) social scientist: the … Read more →

This is the course website for the fall 2022 PS 811 Class […] This is the class website for PS-811 for the 2022 fall semester. PS 811 is a one-credit hour, pass/fail course taught to incoming Ph.D. students in the political science department. This course will be taught remotely; however, RM 3218 in the Social Sciences building has been reserved if you would like to listen to lecture and work on the problem sets together in the room during the class time window. In modern political science, you will be required to perform or understand quantitative research. Often this research is conducted … Read more →

Felix Lennert This is the script for a two-day workshop on data cleaning for the social sciences. I assume you are familiar with basic R concepts such as the different data types and how to index them, the general structure of the syntax, and how to make function calls. In the 21st century, social scientists are able to tap into wells of data that are deeper than ever before. Not only can we use more designed data, i.e., data that have been generated with the clear goal of performing research using them in mind, e.g., survey data, than ever. Also, the rise of the internet as a sensor for … Read more →

This is the workbook you will use for the Quantitative Methods in the Social Sciences lab sessions. […] Welcome to the Quantitative Methods in the Social Sciences lab! This workbook is targeted to University of Glasgow students enrolled in the Undergraduate Quantitative Research Methods course of the School of Social & Political Sciences. The activities are designed for RStudio Cloud. The book was written using R bookdown package based on the GitHub repository: https://github.com/rstudio/bookdown-demo. The online version of this book is licensed under the Creative Commons … Read more →

This book is about relevant social theories that are regularly used in social sciences […] View book source “Social Science Theory” was written by Mike Nguyen. It was last built on 2022-09-27. This book was built by the bookdown R … Read more →

Introduction to R for Data Science: A LISA 2020 Guidebook […] Data science is emerging as a vital skill for researchers, analysts, librarians, and others who deal with data in their personal and professional work. In essence, data science is the application of the scientific method to data for the purpose of understanding the world we live in. More specifically, data science tasks emerge from an interdisciplinary amalgam of statistical analysis, computer science, and social science research conventions. Although other programming languages such as python exceed R in general popularity, R … Read more →

This book serves as an accompanying script for the R sessions of the 2022 Summer Institute for Computational Social Science (SICSS), taking place at the Institut Polytechnique de Paris. […] Dear student, if you read this script, you are either participating in the SICSS itself or came across it while browsing for resources for your studies. In any case, if you find inconsistencies or mistakes, please do not hesitate to point them out by shooting an email to felix.lennert@ensae.fr. This script will introduce you to the automated acquisition and subsequent quantitative analysis of text data … Read more →

Script for the seminar ‘Big Data and Social Science’ at the University of Bern. […] The present document serves both as slides and script for the workshop/seminar Computational Social Science. This seminar is taught by Paul C. Bauer at the University of Mannheim (Spring Semester 2022). The material was developed by Paul C. Bauer and heavily draws on material developed by other people (see script). Any original material and examples is licensed under a Creative Commons Attribution 4.0 International License. For potential future versions of the course see my website: www.paulcbauer.eu. If you … Read more →

Lab notes for Statistics for Social Sciences II: Multivariate Techniques […] Welcome to the lab notes for Statistics for Social Sciences II: Multivariate Techniques. Along these notes we will see how to effectively implement the statistical methods presented in the lectures. The exposition we will follow is based on learning by analyzing datasets and real-case studies, always with the help of statistical software. While doing so, we will illustrate the key insights of some multivariate techniques and the adequate use of advanced statistical software. Be advised that these notes are neither … Read more →

A book created with bookdown. […] This is a book about quantitative analysis using R. The target audience are students in the biological or social sciences learning R and seeking to build professional data science skills, including computer science fundamentals and … Read more →

R @ Ewha (Sunbok Lee) […] Hi everyone, welcome to the course. This is the introduction to R course at Ewha Womans University. R is a great programming language for statistical analysis and data science. I hope you enjoy R in this course and find many useful applications for your own field. This course is designed for students who don’t have any programming background in social science. In this lecture note, this font represents R commands, variable names, and package names. In order to maximize your learning in this semester, you should read the weekly reading assignment in our … Read more →

R @ Ewha (Sunbok Lee) […] “In nonrandomized experiments, it is usually only possible to detemine the existence of a relationship between two measurements, but not the underlying mechanism or the reason for it.” It is known that the best way to investigate causal relationship is to conduct randomized experiments. However, unlike in natural science, it is not easy to conduct randomized experiments in social science because of ethical and practical reasons. The fundamental dilemma of data analysis in social science is that we essentially want to make causal statements in the absence of … Read more →

Introduction to Computational Social Science […] This seminar is intended as a theoretical and methodological introduction to computational social science. Each week covers substantive and theoretical material and is associated with a technical lab. You will need to bring your laptops to each class. In the technical labs you will learn how to analyze network data in R. This e-book contains all of the technical labs in the order that we cover them. Should you forget anything we learned, you will be able to return to this e-book to cover the material again on your … Read more →

Methodology of Social Science & International Relations […] Academic articles have stark differences with the other regular articles. Now using some journals in International Relation field to explain. In morden era, all domestic history are global history.Even before it. Q1: China first meet Greece Culture? Gandhara(犍陀罗) in Buddhism Q2: Suona originally come from? 5th harmony’s “Worth it”,Zurna(唢呐) Q3: David Vases and it’s relation with Chinese porcelian.(元青花) Q4: China first meet Christianity？ Kereit（克烈部）Nestorian Q5: Communist International in China, Otto Braun, … Read more →

Script for the seminar ‘Big Data and Social Science’ at the University of Bern. […] The present document serves both as slides and script for the workshop/seminar Computational Social Science: Theory & Applications. This seminar is taught by Paul C. Bauer at the University of Mannheim (Spring Semester 2021). The material was developed by Paul C. Bauer and heavily draws on material developed by other people (see script). Any original material and examples is licensed under a Creative Commons Attribution 4.0 International License. For potential future versions of the course see my website: … Read more →

The Shape of Polarization: A Topological Data Analysis of Congressional Voting Patterns […] Polarization is a pervasive feature of modern American politics. But has this always been the case? Understanding trends in polarization has been a topic of intense interest in the social sciences, with researchers taking a variety of approaches. The classic strategy has been to use congressional roll call votes and measure the difference in voting patterns between parties (Theriault, 2008; Ladewig, 2010; Shor, 2018; Moskowitz, 2019). More recent work has used text analysis of congressional speech … Read more →

This is a textbook written for an Introduction to Research Methods class in the social sciences […] “The true path to wisdom can be identified … it has to have practical application in your life. Otherwise, wisdom becomes a useless thing and deteriorates, like a sword that is never used.” - Paulo Coelho, “The Pilgrimage” This book is intended as a practical introduction to research methods in the social sciences. If you pursue research academically or professionally, it will probably not be the last book you need to read on the subject. This is intended as something of a gentle introduction … Read more →

This is a guide to the 2017 European Internet Panel Study data set. […] The EIPS is a collaboration between six European probability-based online survey panels. This document gives an overview of the fourth survey, conducted in 2017 (N = 18249). The 2017 joint survey wave was fielded in France by the L’ ́etude longitudinale par internet pour les sciences social sat Sciences Po, in Germany by the German Internet Panel at the University of Mannheim, in Iceland by the Social Science Research Institute Panel (University of Reykjavik), in The Netherlands by the Longitudinal Internet Studies for … Read more →

This project is an effort to connect his Hayes’s conditional process analysis work with the Bayesian paradigm. Herein I refit his models with my favorite R package for Bayesian regression, Bürkner’s brms, and use the tidyverse for data manipulation and plotting. […] Andrew Hayes’s Introduction to Mediation, Moderation, and Conditional Process Analysis text, the second edition of which just came out, has become a staple in social science graduate education. Both editions of his text have been from a frequentist OLS perspective. This project is an effort to connect his work with the Bayesian … Read more →

An R Exercise in Data Collection, Cleaning, and Merging U.S. Census Data […] This document is intended as a follow-along tutorial for learning how to perform data collection and cleaning with R. To the best of my ability, I have tried to make this illustrative of real data and real tasks that anyone from a social science student to a county government official might actually encounter. To that end, I am building upon actual projects that I have worked on as a graduate research assistant to convey this information. For context, previously, I conducted a Mississippi case study of how indoor … Read more →

Script for the seminar ‘Big Data and Social Science’ at the University of Bern. […] The present document serves both as slides and script for the workshop/seminar Big Data and Social Science. This seminar is taught by Paul C. Bauer at the University of Bern (Fall Semester 2018). The material was developed by Paul C. Bauer and heavily draws on material developed by Pablo Barberà in courses such as Social Media & Big Data Research, Big Data Analysis in the Social Sciences and Automated Collection of Web and Social Data. Any original material and examples is licensed under a Creative Commons … Read more →

ggplot2 介紹 […] hypothes.is: https://hypothes.is/groups/eBBqEGde/minicourse-ggplot2 要在hypothes.is貼上程式碼時，請依下例張貼： ggplot2 cheatsheet Computing for the Social Sciences, U.Chicago. ggplot2part of the … Read more →

In 1980 members of the Department of Data Theory at the University of Leiden taught a post-doctoral course in Nonlinear Multivariate Analysis. The course content was sort-of-published, in Dutch, as Gifi (1980). The course was repeated in 1981, and this time the sort-of-published version (Gifi (1981)) was in English. The preface gives some details about the author. The text is the joint product of the members of the Department of Data Theory of the Faculty of Social Sciences, University of Leiden. ‘Albert Gifi’ is their ‘nom de plume’. The portrait, however, of Albert Gifi shown here, is that … Read more →

Big Data and Social Science […] The class on which this book is based was created in response to a very real challenge: how to introduce new ideas and methodologies about economic and social measurement into a workplace focused on producing high-quality statistics. Since the first edition of this book came out we have been fortunate to train over 450 participants in the Applied Data Analytics classes, resulting in increased data analytics capacity, both in terms of human and technical resources. What we learned in delivering these classes greatly influenced the 2nd edition. We also added an … Read more →