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EricJRose83
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Does probability necessitate an underlying deterministic foundation in order to offer a degree of prediction? Thank you in advance!
EricJRose83 said:Okay, is a degree of predictive probability possible if the variables are not computable?
EricJRose83 said:Uh, it's kind of self-evident I would think.
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I think the answer is a resounding yes of course. Seems like a no brainer to me.
I think it is more likely that you are the one who fails "to understand this very simple concept". I can certainly postulate a "probability system" which has 3 possible outcomes, A, B, and C, where the probability of outcome A is 1/2, the probability of putcome B is 1/4, and the provability of outcome C is 1/4. What is the "underlying deterministic system" there?EricJRose83 said:Uh, it's kind of self-evident I would think. Predictive probability is a probability system that offers a degree of prediction. A non-predictive probability system wouldn't offer any prediction and there for by definition wouldn't be a probability system. By degree of prediction, I mean something like 1 in 20 chance of a certain outcome being possible, so on and so forth.
I'm simply asking if a probability system necessitates an underlying deterministic system for it to function properly. If not, then what causes one event to be more probable than another?
I think the answer is a resounding yes of course. Seems like a no brainer to me. However, I've met more people than I can count who either fail to understand this very simple concept or simply disagree without offering up an explanation as to why, but instead say, "I don't understand why a probability system would necessitate an underlying deterministic system".
A probability system is a mathematical model used to determine the likelihood of a certain event or outcome occurring. It involves assigning numerical values, known as probabilities, to various possible outcomes in order to make predictions.
Probability is calculated by dividing the number of desired outcomes by the total number of possible outcomes. This can be represented as a fraction, decimal, or percentage.
The three main types of probability systems are classical, empirical, and subjective. Classical probability is based on theoretical probabilities, empirical probability is based on observed data, and subjective probability is based on personal beliefs and opinions.
Probability systems are used in a variety of fields, including science, finance, and gambling. They help to make predictions and inform decision-making based on the likelihood of certain outcomes.
Probability systems are based on assumptions and can only provide estimates, not exact predictions. They also rely on accurate and unbiased data, which may not always be available. Additionally, probability systems cannot account for unforeseen events or rare occurrences.