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One feature common to all analytical methods is the need for interpretation of the results, usually in a quantifiable way. This book introduces those aspects of statistics and measurement science which help the analytical chemists to produce meaningful results. Among the topics covered are: accuracy and precision, probability and the distribution of error; samples, estimates and hypothesis testing; comparison of means and of standard deviations; statistics of calibration; correlations, statistics in quality control; accuracy and precision in handling, introduction to BASIC are also covered, since many of the routine aspects of data manipulation are now carried out by computer.
A clear and concise introduction and reference for anyone new to the subject of statistics.
Publisher Description
This book provide a comprehensive set of modeling methods for data and uncertainty analysis, taking readers beyond mainstream methods and focusing on techniques with a broad range of real-world applications. The book will be useful as a textbook for graduate students, or as a training manual in the fields of calibration and testing. The work may also serve as a reference for metrologists, mathematicians, statisticians, software engineers, chemists, and other practitioners with a general interest in measurement science.
Education is a hot topic. From the stage of presidential debates to tonight's dinner table, it is an issue that most Americans are deeply concerned about. While there are many strategies for improving the educational process, we need a way to find out what works and what doesn't work as well. Educational assessment seeks to determine just how well students are learning and is an integral part of our quest for improved education. The nation is pinning greater expectations on educational assessment than ever before. We look to these assessment tools when documenting whether students and institutions are truly meeting education goals. But we must stop and ask a crucial question: What kind of assessment is most effective? At a time when traditional testing is subject to increasing criticism, research suggests that new, exciting approaches to assessment may be on the horizon. Advances in the sciences of how people learn and how to measure such learning offer the hope of developing new kinds of assessments-assessments that help students succeed in school by making as clear as possible the nature of their accomplishments and the progress of their learning. Knowing What Students Know essentially explains how expanding knowledge in the scientific fields of human learning and educational measurement can form the foundations of an improved approach to assessment. These advances suggest ways that the targets of assessment-what students know and how well they know it-as well as the methods used to make inferences about student learning can be made more valid and instructionally useful. Principles for designing and using these new kinds of assessments are presented, and examples are used to illustrate the principles. Implications for policy, practice, and research are also explored. With the promise of a productive research-based approach to assessment of student learning, Knowing What Students Know will be important to education administrators, assessment designers, teachers and teacher educators, and education advocates.
This inaugural issue is devoted to exploring measurement, research design, and statistics issues in six subdisciplines of exercise and sport science. Originally presented at the Eighth Measurement and Evaluation Symposium, all papers in this issue reflect the work of many renowned measurement specialists and content experts in their respective fields. The articles discuss the following topics: * standards of assessment quality for physical educators and the problem of providing adequate assessment without adequate resources; * the importance of properly conceptualizing and defining appropriate research questions as the "source and solution" for measurement and design issues in reference to motor learning/control and sport and exercise psychology; * the study of individuals -- single-subject and other small-sample designs -- in contrast to the more traditional study of groups; and * the importance of computing and reporting statistical power in research.
Mismeasurement of explanatory variables is a common hazard when using statistical modeling techniques, and particularly so in fields such as biostatistics and epidemiology where perceived risk factors cannot always be measured accurately. With this perspective and a focus on both continuous and categorical variables, Measurement Error and Misclassi
A textbook oriented toward behavioral and social science students interested in data analysis. This book shows the reader how to do statistical analyses. It also gives examples and situations where a certain statistical test would be used.