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Cover -- Half Title -- Title -- Copyright -- Dedication -- Contents -- List of Tables -- List of Figures -- List of Appendixes -- Preface -- 1 Livestock Systems in Investment and Economic Analysis -- Systems Analysis and Investment Decisionmaking -- Research Methods in Livestock Analysis -- Factors Influencing Livestock Systems -- Approaches to Systems Categorization -- Extensive Versus Intensive Cattle Systems -- Measurements with Animal Units -- Intensive Cattle Systems -- Other Livestock Systems -- 2 Budgeting and Production Economic Theory -- The Budgeting Process -- Production Functions -- Optimal Output -- Production Costs -- 3 Optimization: Marginal Principles and Linear Programming -- How Much Input to Use: Marginal Principles -- Decision Rule Application -- Purebred Dairy Breed Costs and Returns -- Dual-Purpose Breed Costs and Returns -- Discussion -- A Beef Cow/Calf Operation as a Last Example -- Linear Programming in Livestock Production Economics -- Notes -- 4 Cattle Systems in Whole-Farm Analysis -- Whole-Farm Planning -- Description of the Operation -- Weaning at 205 Kilos -- Growing -- Semiconfinement Grain-Finishing Operation -- Forage Finishing -- Combination Forage and Short-Term Grain Finishing -- Integrated System -- 5 Partial Budgeting: Techniques and Application -- The Partial Budgeting Technique -- Early Weaning: An Example -- Preconditioning Calves for Sale to Feedlots -- Supplemental Feeding of Steers on Pasture -- Parasite Control -- Economics of Anabolics -- 6 Economic Analyses in Fattening Cattle to Slaughter Weight -- Types and Economics of Feeding Facilities -- Methods for Carrying out Economic Analyses of Beef Cattle Feeding Trials -- Anabolics and Ionophores in Feedlot Cattle -- Feasibility Studies -- Worldwide Experiences with Feedlots -- Cooperative Feedlots -- 7 Goat and Sheep Systems and Economics.

The concept of automating the testing of software-intensive systems has been around for decades, but the practice of automating testing is scarce in many industries, especially in the government defense sector. A one-year project initiated by the Office of the Secretary of Defense (OSD), Scientific Test and Analysis Techniques Center of Excellence (STAT COE) and sponsored by Navy OPNAV N94 set out to: study the degree to which the Department of Defense (DoD) has adopted automated software testing (AST); share the best software practices used by industry; and develop and distribute an AST implementation guide intended for program management and novice DoD software test automators. The Current State of Automated Software Testing in the Department of Defense, AST Practices and Pitfalls Guide, and the AST Implementation Guide are available at www.afit.edu/stat/

The article of record as published may be found at http://dx.DOI.org/10.1080/08982112.2012.627288 ; The areas of application for design of experiments principles have evolved, mimicking the growth of U.S. industries over the last century, from agriculture to manufacturing to chemical and process industries to the services and government sectors. In addition, statistically based quality programs adopted by businesses morphed from total quality management to Six Sigma and, most recently, statistical engineering (see Hoerl and Snee 2010). The good news about these transformations is that each evolution contains more technical substance, embedding the methodologies as core competencies, and is less of a ''program.'' Design of experiments is fundamental to statistical engineering and is receiving increased attention within large government agencies such as the National Aeronautics and Space Administration (NASA) and the Department of Defense. Because test policy is intended to shape test programs, numerous test agencies have experimented with policy wording since about 2001. The Director of Operational Test & Evaluation has recently (2010) published guidelines to mold test programs into a sequence of well-designed and statistically defensible experiments. Specifically, the guidelines require, for the first time, that test programs report statistical power as one proof of sound test design. This article presents the underlying tenents of design of experiments, as applied in the Department of Defense, focusing on factorial, fractional factorial, and response surface design and analyses. The concepts of statistical modeling and sequential experimentation are also emphasized. Military applications are presented for testing and evaluation of weapon system acquisition, including force-on-force tactics, weapons employment and maritime search, identification, and intercept.