[download pdf] Prediction Revisited: The

Prediction Revisited: The Importance of Observation by Mark P. Kritzman, David Turkington, Megan Czasonis

• Prediction Revisited: The Importance of Observation
• Mark P. Kritzman, David Turkington, Megan Czasonis
• Page: 240
• Format: pdf, ePub, mobi, fb2
• ISBN: 9781119895589
• Publisher: Wiley

Download Prediction Revisited: The Importance of Observation

Free textbook online downloads Prediction Revisited: The Importance of Observation 9781119895589 by Mark P. Kritzman, David Turkington, Megan Czasonis FB2 CHM ePub (English literature)

Overview

A thought-provoking and startlingly insightful reworking of the science of prediction In Prediction Revisited: The Importance of Observation, a team of renowned experts in the field of data-driven investing delivers a ground-breaking reassessment of the delicate science of prediction for anyone who relies on data to contemplate the future. The book reveals why standard approaches to prediction based on classical statistics fail to address the complexities of social dynamics, and it provides an alternative method based on the intuitive notion of relevance. The authors describe, both conceptually and with mathematical precision, how relevance plays a central role in forming predictions from observed experience. Moreover, they propose a new and more nuanced measure of a prediction’s reliability. Prediction Revisited also offers: Clarifications of commonly accepted but less commonly understood notions of statistics Insight into the efficacy of traditional prediction models in a variety of fields Colorful biographical sketches of some of the key prediction scientists throughout history Mutually supporting conceptual and mathematical descriptions of the key insights and methods discussed within With its strikingly fresh perspective grounded in scientific rigor, Prediction Revisited is sure to earn its place as an indispensable resource for data scientists, researchers, investors, and anyone else who aspires to predict the future from the data-driven lessons of the past.

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