Bad data : why we measure the wrong things and often miss the metrics that matter / Peter Schryvers. (Text)Call no.: QA76.9.Q36 S37 2020Publication: Guilford, Connecticut : Prometheus Books, c2020Description: xxiii, 323 pISBN: 9781633885905 (hardcover); 1633885909 (hardcover)Subject(s): Quantitative research -- EvaluationPerformance -- MeasurementLOC classification: QA76.9.Q36 | S37 2020
|Book||Professor Sangvian Indaravijaya Library||General Books||General Stacks||QA76.9.Q36 S37 2020 (เรียกดูชั้นหนังสือ)||ยืมออก||31/01/2021||31379008337579|
Includes bibliographical references and index.
Introduction -- Teaching to the test: Goodhart's Law and the paradox of metrics -- The ins and outs: the logic model and program evaluation -- The long and short of it: intertemporal problems and undervaluing time -- The problem of per: denominator errors -- The forest and the trees: simplifying complex systems -- Apples and oranges: ignoring differing qualities -- Not everything that can be counted counts: the lamppost problem -- Not everything that counts can be counted: measuring what matters -- The measure of metrics -- Gateways not yardsticks.
"Big data is often touted as the key to understanding almost every aspect of contemporary life. This critique of "information hubris" shows that even more important than data is finding the right metrics to evaluate it. The author, an expert in environmental design and city planning, examines the many ways in which we measure ourselves and our world. He dissects the metrics we apply to health, worker productivity, our children's education, the quality of our environment, the effectiveness of leaders, the dynamics of the economy, and the overall well-being of the planet. Among the areas where the wrong metrics have led to poor outcomes, he cites the fee-for-service model of health care, corporate cultures that emphasize time spent on the job while overlooking key productivity measures, overreliance on standardized testing in education to the detriment of authentic learning, and a blinkered focus on carbon emissions, which underestimates the impact of industrial damage to our natural world. He also examines various communities and systems that have achieved better outcomes by adjusting the ways in which they measure data. The best results are attained by those that have learned not only what to measure and how to measure it, but what it all means. By highlighting the pitfalls inherent in data analysis, this illuminating book reminds us that not everything that can be counted really counts."--