Exercises and Solutions in Biostatistical Theory

Salinity affects 10 to 16% of all irrigated lands while the annual rate of land loss due to waterlogging and salinity is about 0.5 million hectares per year. In this dissertation, the role of subsurface drainage to reduce these problems in irrigated agriculture in arid and semi-arid regions has been analysed and challenges for improving subsurface drainage practices have been formulated. Although the installed subsurface drainage systems are in general technically sound and cost-effective, drainage development lags behind irrigation development and consequently a substantial part of the irrigated areas suffers from waterlogging and salinity. This is mainly because the subsurface drainage systems are designed and implemented by government, with the users, the small farmers, having little responsibility and having little input. In the adopted top-down approach the location-specific conditions and farmers preferences are hardly taken into consideration. Furthermore, the emphasis has been on the technical aspects (the physical infrastructure), while the organizational aspects (institutional infrastructure) have been largely neglected.To reverse the negative trend in salt build-up and waterlogging in irrigated lands in semi-arid and arid regions, a number of challenges for enhancing the role of subsurface drainage have been formulated: (i) balancing top-down against bottom-up, (ii) from standardization to flexibility and (iii) focus on capacity development.

Drawn from nearly four decades of Lawrence L. Kupper‘s teaching experiences as a distinguished professor in the Department of Biostatistics at the University of North Carolina, Exercises and Solutions in Biostatistical Theory presents theoretical statistical concepts, numerous exercises, and detailed solutions that span topics from basic probability to statistical inference. The text links theoretical biostatistical principles to real-world situations, including some of the authors own biostatistical work that has addressed complicated design and analysis issues in the health sciences.This classroom-tested material is arranged sequentially starting with a chapter on basic probability theory, followed by chapters on univariate distribution theory and multivariate distribution theory. The last two chapters on statistical inference cover estimation theory and hypothesis testing theory. Each chapter begins with an in-depth introduction that summarizes the biostatistical principles needed to help solve the exercises. Exercises range in level of difficulty from fairly basic to more challenging (identified with asterisks).By working through the exercises and detailed solutions in this book, students will develop a deep understanding of the principles of biostatistical theory. The text shows how the biostatistical theory is effectively used to address important biostatistical issues in a variety of real-world settings. Mastering the theoretical biostatistical principles described in the book will prepare students for successful study of higher-level statistical theory and will help them become better biostatisticians.