How? Using a calibrated mechanical coin tosser.
It turns out you can flip a coin on heads over and over again. Here they concluded that “We conclude that coin tossing is “physics” not “random.” Persi Diaconis and colleagues at Stanford built a mechanical coin tosser as part of the paper named “Dynamical Bias in the coin toss”. This is where our story to understand reality begins. There are two possible options – heads and tails, and heads happen to be one of them. We assume that for a fair coin, each of these possibilities is equal. Probability as a figment of our imaginationĬoming back to our coin toss, by convention we would say the chance of heads appearing on a given coin toss is 1 divided by 2 or 50%. This first got me thinking the idea of probabilities may not be objective but based on subjective experience. If I calculate something to be 60%, a geologist might scrub that off and put it like 30% instead. Geologists, I would notice, would often just overwrite the number and put their own number in “based on experience”. In the oil and gas industry where I worked for 8 years, I would often run elaborate monte carlo simulations to calculate the chance of success (cos) of an oil and gas prospect. Thus, we come up with the 7 divided by 10 (70%) chance. This may look like out of the 10 possible weather scenarios that could happen on a given day, 7 will consist of rain. The probability number is then the total number of scenarios where it could rain divided by the total number of scenarios possible. How did she come to that conclusion? The Weather Bureau will look at patterns in weather historically as well as an understanding of current weather movements to come up with a statistical probability as such. How does that play out in real life? Will it rain tomorrow or not? There is say (for example) a 70% chance it will rain tomorrow the weather analyst may say. Probability and its use in real-life situations This became the main instrument of understanding situations where we have incomplete information about a situation, but the result set is given. Each number had an equal chance of 1/6 (0.166 or 16.67%) appearing in a throw of the die. Thus, was born the idea of equal chances of the numbers 1 to 6 occurring in a fair six-sided die.
#Facade coin flip series#
Both formalised the problem in a series of letters which is now known as Probability theory. He proposed this particular problem to the mathematicians’ Pascal and Fermat of dividing a stake between two players which was interrupted before it was closed. The story as to how this field of mathematics was born goes back to a French gambler named Chevalier De Mere in 1654. The World of Different Realities: AR, MR and VR.RPA, Intelligent Automation & Data Analytics.AI in Healthcare: Perspectives on a Changing Sector.Why Metaverse May Disrupt Banking & FinTech Sooner Than We Expect.Vision Based Perception Expands Mobile Robot Capabilities.Are you ready to make the quantum leap?.Is automation tech the ‘secret sauce’ to de-stress employees?.The key myths impeding AI and Machine Learning success – and why there’s no truth in them.Beyond the Hype: Understanding the True Value of AI/ML in Security Environments.
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