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portada Personality Traits and Drug Consumption: A Story Told by Data (Springerbriefs in Statistics)
Type
Physical Book
Publisher
Author
Year
2019
Language
English
Pages
168
Format
Hardcover
ISBN13
9783030104412
Edition No.
1
Categories

Personality Traits and Drug Consumption: A Story Told by Data (Springerbriefs in Statistics)

Elaine Fehrman; Vincent Egan; Alexander N. Gorban; Jeremy Levesley; Evgeny M. Mirkes; Awaz K. Muhammad (Author) · Springer · Hardcover

Personality Traits and Drug Consumption: A Story Told by Data (Springerbriefs in Statistics) - Elaine Fehrman; Vincent Egan; Alexander N. Gorban; Jeremy Levesley; Evgeny M. Mirkes; Awaz K. Muhammad

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Synopsis "Personality Traits and Drug Consumption: A Story Told by Data (Springerbriefs in Statistics) "

This book discusses the psychological traits associated with drug consumption through the statistical analysis of a new database with information on 1885 respondents and use of 18 drugs. After reviewing published works on the psychological profiles of drug users and describing the data mining and machine learning methods used, it demonstrates that the personality traits (five factor model, impulsivity, and sensation seeking) together with simple demographic data make it possible to predict the risk of consumption of individual drugs with a sensitivity and specificity above 70% for most drugs. It also analyzes the correlations of use of different substances and describes the groups of drugs with correlated use, identifying significant differences in personality profiles for users of different drugs. The book is intended for advanced undergraduates and first-year PhD students, as well as researchers and practitioners. Although no previous knowledge of machine learning, advanced data mining concepts or modern psychology of personality is assumed, familiarity with basic statistics and some experience in the use of probabilities would be helpful. For a more detailed introduction to statistical methods, the book provides recommendations for undergraduate textbooks.

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