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How To Lie With Coronavirus Statistics: Campbell's Law And Measuring The Effects Of Covid-19, Joel Best

Numeracy

Campbell's Law warns that when measurements become consequential those whose performance is being measured may try to skew the results. This case study examines the Trump administration's efforts to present COVID-19 statistics that would discourage restricting economic activities and encourage reopening the economy.

Bayesian Reliability Analysis For Optical Media Using Accelerated Degradation Test Data, Kun Bu

USF Tampa Graduate Theses and Dissertations

ISO (the International Organization for Standardization) 10995:2011 is the inter-national standard providing guidelines for assessing the reliability and service life of optical media, which is designed to be highly reliable and possesses a long lifetime. A well-known challenge of reliability analysis for highly reliable devices is that it is hard to obtain sufficient failure data under their normal use conditions. Accelerated degradation tests (ADTs) are commonly used to quickly obtain physical degradation data under elevated stress conditions, which are then extrapolated to predict reliability under the normal use condition. This standard achieves the estimation of the lifetime of recordable media, …

Art, Artfulness, Or Artifice?: A Review Of The Art Of Statistics: How To Learn From Data, By David Spiegelhalter, Jason Makansi

Numeracy

David Spiegelhalter. 2019. The Art of Statistics: How to Learn From Data. (London: The Penguin Group). 444 pp. ISBN 978-1541618510

The author successfully eases the reader away from the rigor of statistical methods and calculations and into the realm of statistical thinking. Despite an engaging style and attention-grabbing examples, the reader of The Art of Statistics will need more than a casual grounding in statistics to get what Spiegelhalter, I believe, intends from his book. It should be viewed as a companion to a more rigorous textbook on statistical methods but not necessarily a book that makes statistics any …

Dubious Data And Difficult Conversations: Review Of No Bs (Bad Stats): Black People Need People Who Believe In Black People Enough Not To Believe Every Bad Thing They Hear About Black People, By Ivory A. Toldson., Joel Best

Numeracy

Ivory A. Toldson. 2019. No BS (Bad Stats): Black People Need People Who Believe in Black People Enough Not to Believe Every Bad Thing They Hear about Black People; (Boston, Brill). Paperback ISBN 978-90-04-39702-6. E-book ISBN 978-90-04-39704-0.

Ivory A. Toldson is a professor of Counseling Psychology at Howard University and the current editor-in-chief of the Journal of Negro Education (founded in 1932), and offers an unapologetic critique of how statistical malpractice has misrepresented the situation of Blacks in the United States. Readers of Numeracy should find his examples and analysis both interesting and thought-provoking.

The Author’S Reflections On No B.S. (Bad Stats): Black People Need People Who Believe In Black People Enough Not To Believe Every Bad Thing They Hear About Black People, Ivory A. Toldson

Numeracy

Toldson, Ivory. A. 2019. No BS (Bad Stats): Black People Need People Who Believe in Black People Enough Not to Believe Every Bad Thing They Hear About Black People (Boston, MA: Brill-Sense) 194 pp. ISBN 978-9004397026.

This essay provides an introduction to No BS (Bad Stats): Black People Need People Who Believe in Black People Enough Not to Believe Every Bad Thing They Hear About Black People. In the essay, the author discusses how cynical views about the educational potential of Black children motivated him to write a book that challenges negative statistics. The essay also outlines the harmful …

Gradient Boosting For Survival Analysis With Applications In Oncology, Nam Phuong Nguyen

USF Tampa Graduate Theses and Dissertations

Cancer is one of the most deadly diseases that the world has been fighting against over decades. An enormous number of research has been conducted, via a wide scale of approaches, raging from genetic analysis to mathematical modeling. Survival analysis is a well-performed methodology frequently used to estimate the survival probability of a patient. Although there has been a large number of methods for survival analysis, efficient exploration of a high-dimensional feature space has been challenging due to its computational cost and complexity. This thesis adapts the component-wise gradient boosting algorithms for cancer survival analysis, and also proposes a new …