This book is designed to provide a comprehensive introduction to R programming for data analysis, manipulation and presentation. It covers fundamental data structures such as vectors, matrices, arrays and lists, along with techniques for exploratory data analysis, data transformation and manipulation. The book explains basic statistical concepts and demonstrates their implementation using R, including descriptive statistics, graphical representation of data, probability, popular probability distributions and hypothesis testing. It also explores linear and non-linear modeling, model selection and diagnostic tools in R. The book also covers flow control and conditional calculations by using ‘‘if’’ conditions and loops and discusses useful functions and resources for further learning. It provides an extensive list of functions grouped according to statistics classification, which can be helpful for both statisticians and R programmers. The use of different graphic devices, high-level and low-level graphical functions and adjustment of parameters are also explained. Throughout the book, R commands, functions and objects are printed in a different font for easy identification. Common errors, warnings and mistakes in R are also discussed and classified with explanations on how to prevent them.
This book introduces a number of new sampling plans, such as time truncated life tests, skip sampling plans, resubmitted plans, mixed sampling plans, sampling plans based on the process capability index and plans for big data, which can be used for testing and inspecting products, from the raw-materials stage to the final product, in every industry using statistical process control techniques. It also presents the statistical theory, methodology and applications of acceptance sampling from truncated life tests. Further, it discusses the latest reliability, quality and risk analysis methods based on acceptance sampling from truncated life, which engineering and statisticians require in order to make decisions, and which are also useful for researchers in the areas of quality control, lifetime analysis, censored data analysis, goodness-of-fit and statistical software applications. In its nine chapters, the book addresses a wide range of testing/inspection sampling schemes for discrete and continuous data collected in various production processes. It includes a chapter on sampling plans for big data and offers several illustrative examples of the procedures presented. Requiring a basic knowledge of probability distributions, inference and estimation, and lifetime and quality analysis, it is a valuable resource for graduate and senior undergraduate engineering students, and practicing engineers, more specifically it is useful for quality engineers, reliability engineers, consultants, black belts, master black belts, students and researchers interested in applying reliability and risk and quality methods.
This book focuses on early germination, one of maize germplasm most important strategies for adapting to drought-induced stress. Some genotypes have the ability to adapt by either reducing water losses or by increasing water uptake. Drought tolerance is also an adaptive strategy that enables crop plants to maintain their normal physiological processes and deliver higher economical yield despite drought stress. Several processes are involved in conferring drought tolerance in maize: the accumulation of osmolytes or antioxidants, plant growth regulators, stress proteins and water channel proteins, transcription factors and signal transduction pathways. Drought is one of the most detrimental forms of abiotic stress around the world and seriously limits the productivity of agricultural crops. Maize, one of the leading cereal crops in the world, is sensitive to drought stress. Maize harvests are affected by drought stress at different growth stages in different regions. Numerous events in the life of maize crops can be affected by drought stress: germination potential, seedling growth, seedling stand establishment, overall growth and development, pollen and silk development, anthesis silking interval, pollination, and embryo, endosperm and kernel development. Though every maize genotype has the ability to avoid or withstand drought stress, there is a concrete need to improve the level of adaptability to drought stress to address the global issue of food security. The most common biological strategies for improving drought stress resistance include screening available maize germplasm for drought tolerance, conventional breeding strategies, and marker-assisted and genomic-assisted breeding and development of transgenic maize. As a comprehensive understanding of the effects of drought stress, adaptive strategies and potential breeding tools is the prerequisite for any sound breeding plan, this brief addresses these aspects.
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