Sentence examples for history of probability from inspiring English sources

Daniel Kahneman and Amos Tversky's Prospect theory (1979) is to be situated in the history of probability and rational choice theory, as well as in a twentieth century American context of social engineering.

She has published on a wide range of topics in the history of science, including the history of probability and statistics, the emergence of the scientific fact and objects of scientific inquiry.

The problem of approximate computation of probabilities that are known in principle is a recurrent theme throughout the history of probability theory and will be discussed in more detail below.

The book is structured into two parts, the first one dealing with the history of probability and its impact on social sciences, and the second one, conversely, with how advances in social sciences influenced the developments of probability theory.

These two parts are preceded by a General Introduction to the whole volume, which outlines the history of probability and social sciences, in particular since the 17th century, and provides the reader with a roadmap through the entire book.

She has written on a wide range of topics in the history of science, including the history of probability and statistics, wonders in early-modern science, and the history of scientific objectivity.

NOVA's Prediction by the Numbers on PBS explores the history of probabilities and explains how early theories about gambling have led to extensive high-level thinking using mathematics and data.

A recent comment on the history of imprecise probabilities can be found in Vicig and Seidenfeld (2012).

Luck, risk, and life chances This chapter explores the history and development of probability and statistics as applied resources.

… In summary, this book is a very welcome compendium on the history and perspectives of probability and social sciences, brought together in one volume, which can be fully recommended especially for academics and doctoral students of quantitative social sciences.

The risk of lung cancer under each intervention is estimated as a weighted sum (or integral), over exposure and covariate histories, of the probability of lung cancer conditional on exposure and covariates.