Straightforward, clear, and applied, this book will give you the theoretical and practical basis you need to apply data analysis techniques to real data. Combining key statistical concepts with detailed technical advice, it addresses common themes and problems presented by real research, and shows you how to adjust your techniques and apply your statistical knowledge to a range of datasets. It also embeds code and software output throughout and is supported by online resources to enable practice and safe experimentation. The book includes: * Original case studies and data sets * Practical exercises and lists of commands for each chapter * Downloadable Stata programmes created to work alongside chapters * A wide range of detailed applications using Stata * Step-by-step guidance on writing the relevant code. This is the perfect text for anyone doing statistical research in the social sciences getting started using Stata for data analysis.

War describes a situation of armed conflict between two or more parties. There are several ways in which we can classify wars. The major division in the academic literature is between interstate wars and civil wars. The former is fought out between two or more states; the latter between groups belonging to the same state. There exists a vast literature, a large part of it quantitative, on both types of conflict. The majority of wars are civil wars. This book introduces the reader to the concept of war, and also to the different schools of thought as well as to the research methods pertaining to this area of research. It is an edited book containing articles written by several causes of war researchers. War is an important subject of study. The nature of war has changed over time, leaving the civilian population increasingly vulnerable. It has negative impacts beyond the direct casualties and the damaged infrastructure and economy in the countries in question. This book is intended to reach a wide audience, ranging from Bachelor and Master students in the social sciences, as well as to researchers and others with an interest for the subject. The aim of this work is both to give an outline of the literature, as well as providing examples of different schools of thought within the causes of war' literature. It gives the reader a comprehensive account of the research on causes of war', ranging from the old classics, like e.g., Clausewitz and Sun Tzu, to up-to-date research. The contributors in this book are chosen to represent a variety of perspectives on the causes of conflict.

This book employs quantitative methods to test the effect of human rights abuses on civil war onset. Its point of departure is the classic theories of collective violence, namely the deprived actor (DA) and rational actor (RA) research traditions. I find that in ethnically fractionalized societies, state repression decreases the risk of civil war. This gives support to the RA assumption that repression (which produce grievances) in ethnically fractionalized societies (which are the most conflict prone) should not lead to an increased probability of civil war onset. Thus, grievance is not the deciding factor for why people resort to violence.

Straightforward, clear, and applied, this book will give you the theoretical and practical basis you need to apply data analysis techniques to real data. Combining key statistical concepts with detailed technical advice, it addresses common themes and problems presented by real research, and shows you how to adjust your techniques and apply your statistical knowledge to a range of datasets. It also embeds code and software output throughout and is supported by online resources to enable practice and safe experimentation. The book includes: * Original case studies and data sets * Practical exercises and lists of commands for each chapter * Downloadable Stata programmes created to work alongside chapters * A wide range of detailed applications using Stata * Step-by-step guidance on writing the relevant code. This is the perfect text for anyone doing statistical research in the social sciences getting started using Stata for data analysis.