POLS-296 Quantitative Methods: Getting Help with using R Statistical Software

Data Wrangling with R by Gustavo R. Santos No detailed description available for "Data Wrangling with R".

Understanding and Applying Basic Statistical Methods Using R by Rand R. Wilcox Features a straightforward and concise resource for introductory statistical concepts, methods, and techniques using R  Understanding and Applying Basic Statistical Methods Using R uniquely bridges the gap between advances in the statistical literature and methods routinely used by non-statisticians. Providing a conceptual basis for understanding the relative merits and applications of these methods, the book features modern insights and advances relevant to basic techniques in terms of dealing with non-normality, outliers, heteroscedasticity (unequal variances), and curvature. Featuring a guide to R, the book uses R programming to explore introductory statistical concepts and standard methods for dealing with known problems associated with classic techniques. Thoroughly class-room tested, the book includes sections that focus on either R programming or computational details to help the reader become acquainted with basic concepts and principles essential in terms of understanding and applying the many methods currently available. Covering relevant material from a wide range of disciplines, Understanding and Applying Basic Statistical Methods Using R also includes: Numerous illustrations and exercises that use data to demonstrate the practical importance of multiple perspectives  Discussions on common mistakes such as eliminating outliers and applying standard methods based on means using the remaining data Detailed coverage on R programming with descriptions on how to apply both classic and more modern methods using R  A companion website with the data and solutions to all of the exercises  Understanding and Applying Basic Statistical Methods Using R is an ideal textbook for an undergraduate and graduate-level statistics courses in the science and/or social science departments. The book can also serve as a reference for professional statisticians and other practitioners looking to better understand modern statistical methods as well as R programming. Rand R. Wilcox, PhD, is Professor in the Department of Psychology at the University of Southern California, Fellow of the Association for Psychological Science, and an associate editor for four statistics journals. He is also a member of the International Statistical Institute. The author of more than 320 articles published in a variety of statistical journals, he is also the author eleven other books on statistics. Dr. Wilcox is creator of WRS (Wilcox' Robust Statistics), which is an R package for performing robust statistical methods. His main research interest includes statistical methods, particularly robust methods for comparing groups and studying associations.  

Handbook on Impact Evaluation by Shahidur R. Khandker; Gayatri B. Koolwal; Hussain A. Samad Public programs are designed to reach certain goals and beneficiaries. Methods to understand whether such programs actually work, as well as the level and nature of impacts on intended beneficiaries, are main themes of this book. Has the Grameen Bank, for example, succeeded in lowering consumption poverty among the rural poor in Bangladesh? Can conditional cash transfer programs in Mexico and Latin America improve health and schooling outcomes for poor women and children? Does a new road actually raise welfare in a remote area in Tanzania, or is it a 'highway to nowhere'? This book reviews quantitative methods and models of impact evaluation. It begins by reviewing the basic issues pertaining to an evaluation of an intervention to reach certain targets and goals. It then focuses on the experimental design of an impact evaluation, highlighting its strengths and shortcomings, followed by discussions on various non-experimental methods. The authors also cover methods to shed light on the nature and mechanisms by which different participants are benefiting from the program. For researchers interested in learning how to use these models with statistical software, the book also provides STATA exercises in the context of evaluating major microcredit programs in Bangladesh, such as the Grameen Bank. The framework presented in this book can be very useful for strengthening local capacity in impact evaluation among technicians and policymakers in charge of formulating, implementing, and evaluating programs to alleviate poverty and underdevelopment.