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Taking a simplified approach to statistics, this textbook teaches students the skills required to conduct and understand quantitative research. It provides basic mathematical instruction without compromising on analytical rigor, covering the essentials of research design; descriptive statistics; data visualization; and statistical tests including t-tests, chi-squares, ANOVAs, Wilcoxon tests, OLS regression, and logistic regression. Step-by-step instructions with screenshots are used to help students master the use of the freely accessible software R Commander. Ancillary resources include a solutions manual and figure files for instructors, and datasets and further guidance on using STATA and SPSS for students. Packed with examples and drawing on real-world data, this is an invaluable textbook for both undergraduate and graduate students in public administration and political science.
This accessible and practical textbook gives students the perfect guide to the use of regression models in testing and evaluating hypotheses dealing with social relationships. A range of statistical methods suited to a wide variety of dependent variables is explained, which will allow students to read, understand, and interpret complex statistical analyses of social data. Each chapter contains example applications using relevant statistical methods in both Stata and R, giving students direct experience of applying their knowledge. A full suite of online resources - including statistical command files, datasets and results files, homework assignments, class discussion topics, PowerPoint slides, and exam questions - supports the student to work independently with the data, and the instructor to deliver the most effective possible course. This is the ideal textbook for advanced undergraduate and beginning graduate students taking courses in applied social statistics.
In this chapter, I test the theory of the effect of colonial indirect rule on postcolonial insurgency using an all-India district-level dataset. I use unique Ministry of Home Affairs (MHA) data as a measure of the dependent variable of Maoist control. Unlike other quantitative studies of Maoist insurgency that use measures of violence from 2005 to 2010 as their dependent variable, I do not use such violence data as my dependent variable since violence is only the most visible aspect of insurgency and does not measure actual Maoist rebel control, which is a more multidimensional concept. There is potential bias in the OLS regression estimates since the British possibly selected those districts for indirect rule that were worse off in terms of revenue and productivity. To correctly estimate the causal effect of colonial indirect rule, I control for some observable pre-colonial determinants of indirect rule choice, like forest cover, terrain, soil quality, and pre-colonial agrarian rebellion and find that princely state is still a statistically significant predictor of Maoist control. While these pre-colonial qualities may have played a role in the choice of institutions, once in place such colonial indirect rule had an independent causal effect on postcolonial insurgency.
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