Proof of the Dangers of Gambling (Based on the Analysis of Problems in Probability Theory)
Keywords:
Gambling, Probability theory, Law of large numbers, Expected value, Casino strategies, Financial and psychological risks, Gambling addiction, Markov chains, Statistical modelingAbstract
This study is dedicated to proving the dangers of gambling based on probability theory. Since gambling is fundamentally based on randomness, mathematical evidence demonstrates that, in the long run, it is economically disadvantageous for players. The research explores key principles of probability theory, including the law of large numbers, expected value, variance, and Markov chains. Additionally, the mechanisms behind casinos and betting systems are analyzed, showing through statistical modeling how they are inherently structured to be unfavorable for players.
The study reveals that players’ perception of "winning chances" often does not align with real probabilistic outcomes, leading to significant psychological and financial risks. Moreover, the research examines the social impact of gambling addiction and evaluates players’ cognitive biases regarding wins and losses. This study aims to highlight the dangers of gambling from a probability theory perspective while promoting financial literacy and informed decision-making.
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Copyright (c) 2025 Oralbek Yerulan, Kazez Ertai
This work is licensed under a Creative Commons Attribution 4.0 International License.
