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Absolutely no judgment or evaluation should be included when reporting a reliability analysis. Estimates should speak for themselves and it is the task of the readers to judge their values. The discussion should focus on limitations of analysis. In this chapter, example discussions for the Benchmark Assessment of English Language Arts (ELA), the Palmetto Achievement Challenge Test (PACT) of mathematics, and the MSCAN are provided. Several books for future reading are recommended. These include books on classical test theory. Some of the recommended book include Theory of Mental Tests by Gulliksen, Statistical Theories of Mental Test Scores by Lord and Novick, and Reliability for the Social Sciences: Theory and Applications by Traub. The chapter also advises that reading be done on original references so that one can read the original words of the author. Other references are given after this chapter.

Chapter 13 of Performing Music Research outlines a range of statistical approaches designed to identify associations (or “relationships”) between variables. it starts with correlation and regression, which allow the nature and strength of the relationships between two or more variables to be quantified. Next, it considers approaches with specific applications: analyzing relationships between categorical variables; testing the reliability of questionnaires and raters; reducing a large number of variables to a smaller number of underlying factors; and understanding complex interactions within networks of variables. The chapter sets out examples of the situations in which each test can be used, provides guidance on conducting it using standard statistical software, and advises on how best to interpret and report its results.

Risk models provide the roadmaps that guide the analyst throughout the journey of risk assessment, if the adage ‘To manage risk, one must measure it’ constitutes the compass for risk management. The process of risk assessment and management may be viewed through many lenses, depending on the perspective, vision, values, and circumstances. This chapter addresses the complex problem of coping with catastrophic risks by taking a systems engineering perspective. Systems engineering is a multidisciplinary approach distinguished by a practical philosophy that advocates holism in cognition and decision making. The ultimate purposes of systems engineering are to (1) build an understanding of the system’s nature, functional behaviour, and interaction with its environment, (2) improve the decision-making process (e.g., in planning, design, development, operation, and management), and (3) identify, quantify, and evaluate risks, uncertainties, and variability within the decision-making process. Engineering systems are almost always designed, constructed, and operated under unavoidable conditions of risk and uncertainty and are often expected to achieve multiple and conflicting objectives. The overall process of identifying, quantifying, evaluating, and trading-off risks, benefits, and costs should be neither a separate, cosmetic afterthought nor a gratuitous add-on technical analysis. Rather, it should constitute an integral and explicit component of the overall managerial decision-making process. In risk assessment, the analyst often attempts to answer the following set of three questions (Kaplan and Garrick, 1981): ‘What can go wrong?’, ‘What is the likelihood that it would go wrong?’, and ‘What are the consequences?’ Answers to these questions help risk analysts identify, measure, quantify, and evaluate risks and their consequences and impacts. Risk management builds on the risk assessment process by seeking answers to a second set of three questions (Haimes, 1991): ‘What can be done and what options are available?’, ‘What are their associated trade-offs in terms of all costs, benefits, and risks?’, and ‘What are the impacts of current management decisions on future options?’ Note that the last question is the most critical one for any managerial decision-making.