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Hot on the heals of the award-winning and best selling Discovering Statistics Using SPSS, Third Edition, Andy Field has teamed up with Jeremy Miles (co-author of Discovering Statistics Using SAS) to write Discovering Statistics Using R. Keeping the uniquely humorous and self-depreciating style that has made students across the world fall in love with Andy Field's books, Discovering Statistics Using R takes students on a journey of statistical discovery using the freeware R, a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences throughout the world. The journey begins by explaining basic statistical and research concepts before a guided tour of the R software environment. Next the importance of exploring and graphing data will be discovered, before moving onto statistical tests that are the foundations of the rest of the book (for e.g. correlation and regression). Readers will then stride confidently into intermediate level analyses such as ANOVA, before ending their journey with advanced techniques such as MANOVA and multilevel models. Although there is enough theory to help the reader gain the necessary conceptual understanding of what they're doing, the emphasis is on applying what's learned to playful and real-world examples that should make the experience more fun than expected. Like its sister textbooks, Discovering Statistics Using R is written in an irreverent style and follows the same ground-breaking structure and pedagogical approach. The core material is augmented by a cast of characters to help the reader on their way, hundreds of examples, self-assessment tests to consolidate knowledge, and additional website material for those wanting to learn more (at www.sagepub.co.uk/fieldandmilesR). Given this book's accessibility, fun spirit, and use of bizarre real-world research it should be essential for anyone wanting to learn about statistics using the freely-available R software.
(source: Nielsen Book Data)

To help Air Force Services tailor support for Airmen and their families through analyses of the relevance of neighborhood, or area, characteristics of major Air Force installations located within the United States, researchers applied established social indicators and neighborhood methodology to identify which areas may have greater need for Air Force resources. This document reports the results of that analysis. It examines whether and how base-area characteristics are associated with individual-level Airman outcomes across several different domains. The objective is to help the Air Force identify communities where Airmen and their families may have greater levels of need so that it can adapt programs or resources to counteract stressors related to the base areas and the lack of nonmilitary resources in the area. Using census and personnel data, the authors created a set of area profiles that make up the RAND Base Area Social and Economic Index, or RAND BASE-I, measuring aspects of household composition, employment, income and poverty, housing, social, and transportation of area residents (both military and civilian). These factors are outside of Air Force control; however, Air Force Services may be able to help offset potential negative impacts of community characteristics on Airmen and their families. Using existing Air Force survey data, the authors then assessed whether these base-area characteristics were associated with Airmen's outcomes related to health and well-being, military and neighborhood cohesion, ratings of neighborhood resources, use of on-base resources, satisfaction, and career intentions. The analysis also tested whether Airmen who live off base and commute to work may be more exposed to social and economic conditions in the larger base area than Airmen who primarily live and work on base.