A framing case study discusses European Union trade rules that ban the sale of all products made from seals. Then the chapter provides an overview of international trade law. The chapter discusses: (1) how states have historically promoted international law, including major concepts and the evolution of trade institutions; (2) major obligations under contemporary trade law, including rules for market access and treatment standards; and (3) major exceptions under trade law that allow states to restrict trade to prevent unfair trade, safeguard economies from unexpected shocks, protect competing values (like human health and the environment), and preserve national security.

A framing case study examines South Africa’s allegation in early 2024 that Israel committed genocide in Gaza. Then the chapter examines: (1) the history of international law, from ancient societies through the Middle Ages and the classical, positivist, and modern eras; (2) important actors in international law, including states, international organizations, peoples (groups), individuals, and non-governmental groups; and (3) the critical, contractual, and sociological perspectives on how international law can influence politics.

A framing case study describes the 2018 surge of migrants attempting to cross the English Channel from continental Europe to the UK in small boats to seek refugee status. The chapter then discusses international migration law. The chapter begins by presenting important concepts and historical trends from migration law, and the competing models of economic migration and crisis migration. It then describes in detail major components of the Refugee Convention, which sets international rules for determining whether an individual can be a refugee, creates rights for refugees, and shapes subsequent outcomes for individuals who are denied or lose refugee status. Finally, the chapter examines how international migration law interacts with topics discussed earlier in the book, including: law of the sea, human rights, armed conflict, criminal law, and environmental law.

A framing case study compares military action involving two hospitals in two different wars: an Israeli raid on Al-Shifa Hospital in Gaza in November 2023, and Russia’s bombing of Okhmatdyt Children’s Hospital in Ukraine in July 2024. Then the chapter examines the law of armed conflict. The chapter first discusses major principles of armed conflict and the historical evolution of treaty law. It next discusses protected people by describing how international law distinguished between civilians and combatants, and how this law provides certain protections to each group. The chapter then discusses various laws regulating military conduct, including: how states choose targets; methods of war; weapons; and the rules of belligerent occupation. Finally, the chapter briefly surveys the specialized rules that apply to non-international armed conflict.

This chapter demonstrates R’s capabilities for statistical analysis and data science applications. It covers data importing from CSV/TSV files into R dataframes and computing basic statistics (mean, median, mode, variance, standard deviation) using built-in functions.

The chapter explores data visualization with ggplot2, creating histograms, bar charts, pie charts, and scatterplots for effective data presentation. Key statistical concepts include correlation analysis to measure variable relationships and statistical inference through hypothesis testing.

Practical statistical tests covered include t-tests for comparing two group means and ANOVA for comparing multiple groups. The chapter emphasizes R’s strengths in statistical computing, providing hands-on examples with real datasets and demonstrating how to interpret results for data-driven decision making.

Posters, presentations, and publications are the three main ways to circulate your research for feedback and dispersion. Each has strengths and weaknesses. Posters require you to be concise and graphical, but they allow extensive interaction with the audience. Fortunately, powerful software designed for presentations facilitates good graphic design even for novices. Presentations, on the other hand, can be somewhat longer and less graphic than posters, but they also come at the cost of more limited audience feedback. Finally, publication is the usual end-state of a piece of research; its strengths are its permanence and circulation, but its costs for undergraduates often include significant time for revisions, delays in publication, and weak feedback from reviewers. Options for continued study and involvement in political science research include master’s degrees, which are typically more applied and policy oriented, and PhD (doctoral) programs, which are research oriented.

This introductory chapter defines data science as a field focused on collecting, storing, and processing data to derive meaningful insights for decision-making. It explores data science applications across diverse sectors including finance, healthcare, politics, public policy, urban planning, education, and libraries. The chapter examines how data science relates to statistics, computer science, engineering, business analytics, and information science, while introducing computational thinking as a fundamental skill. It discusses the explosive growth of data (the 3Vs: velocity, volume, variety) and essential skills for data scientists, including statistical knowledge, programming abilities, and data literacy. The chapter concludes by addressing critical ethical concerns around privacy, bias, and fairness in data science practice.

This chapter introduces R, a free, open-source programming environment designed for data analysis and statistical computing. It covers R installation through RStudio IDE and demonstrates fundamental programming concepts including basic syntax, mathematical operations, and logical operators.

Key topics include data types (numeric, integer, character, logical, factor), data structures (vectors, matrices, lists), control structures (if-else statements, for/while loops), and functions for code organization and reusability.

The chapter emphasizes R’s advantages for data science: powerful statistical capabilities, extensive package ecosystem, and built-in data handling features. It concludes with R Markdown, which enables creation of professional reports combining code, output, and documentation in a single document for reproducible research and presentation.

A framing case study examines Chinese militarization of the Spratly Islands, located in the South China Seas. Then the chapter provides an overview of the law of the sea. The chapter discusses: (1) the historical evolution of rules that govern the sea, including principles of customary international law; (2) how states have used modern treaties to create zones of authority, including maritime zones, water rights, and seabed rights; and (3) how states resolve maritime boundary disputes.

This chapter explores supervised learning techniques where algorithms learn from labeled training data to make predictions. It begins with logistic regression for binary classification problems, using the sigmoid function to output probabilities between 0 and 1. Softmax regression extends this to multi-class problems. The chapter covers k-nearest neighbors (kNN), which classifies data points based on their similarity to training examples. Decision trees use entropy and information gain to create interpretable classification rules, while random forests combine multiple decision trees to reduce overfitting through ensemble methods. Naive Bayes applies Bayes’ theorem with independence assumptions for probabilistic classification, particularly effective for text classification. Finally, support vector machines (SVM) find optimal decision boundaries by maximizing margins between classes. Each technique is demonstrated through hands-on Python examples using real datasets, showing practical applications in various domains from healthcare to finance.