Kevin's Bacon on Nostr: I'm watching Hoppe talk about probability theory, and I'm sorry, he's wrong, but he's ...
I'm watching Hoppe talk about probability theory, and I'm sorry, he's wrong, but he's onto something. Probability theory is not exclusively limited to the domain of objective, empirically verifiable facts of frequency.
For an individual, one time event, the probability indicates the likelihood of the event occurring, given the knowledge available to the observer and the time period chosen, **just like it does over a longer period of time with multiple events of a given class.** This is what probability means. What Hoppe is observing but failing to fully grasp is that the frequency of the event becomes indefinite as the number of events gets very small or as the time to observe them gets small, and that the subjective evaluation of likelihood therefore has no basis of prior events of this exact type on which to draw. It still may have a basis, utilizing other knowledge regarding its likelihood. Regardless of where the basis comes from, this knowledge and synthesis into a subjective likelihood is exactly what probability estimation is, whether using objective empirical measurements of frequency or not. This is simply one of the inputs for probability estimations.
Because this is one of the most important inputs into a probability, intersubjective measurements of the probability for a single event varies much more between observers than the same intersubjective variance of opinion for a collection of these events that has been empirically measured. The longer the time of data collection, the more definite the frequency. Thus as the frequency component of an event's tendency to occur becomes less definite (which happens as the collection of events approaches one single occurrence within a given time frame), the observer's particular knowledge, characteristics, and relationship to the event become more and more relavent to the measurement or approximation of probability made, an approximation which was always subject to the knowledge of the individual observer.
Moving in the direction of longer time periods and larger datasets, with many repeatedly observed events, intersubjective assessments of both frequency and therefore probability, become more clear. The measurements made for frequency are objective in the sense that they really are true and meaningful from the observer's chosen reference timeframe and universe being observed, and they also tend to corroborate with other observers. This is objective frequency and could be considered "objective probability." But probability is, as I stated, referring to the _likelihood_ of this event occurring over a timeframe given, which becomes certain for events in the past that have been measured with certainty or that are guaranteed to happen in the future, and is subjective based on those which are approximated because they are yet to occur, or had to be inferred with error, or have been measured with error.
#ProbabilityTheory #HansHermannHoppe
For an individual, one time event, the probability indicates the likelihood of the event occurring, given the knowledge available to the observer and the time period chosen, **just like it does over a longer period of time with multiple events of a given class.** This is what probability means. What Hoppe is observing but failing to fully grasp is that the frequency of the event becomes indefinite as the number of events gets very small or as the time to observe them gets small, and that the subjective evaluation of likelihood therefore has no basis of prior events of this exact type on which to draw. It still may have a basis, utilizing other knowledge regarding its likelihood. Regardless of where the basis comes from, this knowledge and synthesis into a subjective likelihood is exactly what probability estimation is, whether using objective empirical measurements of frequency or not. This is simply one of the inputs for probability estimations.
Because this is one of the most important inputs into a probability, intersubjective measurements of the probability for a single event varies much more between observers than the same intersubjective variance of opinion for a collection of these events that has been empirically measured. The longer the time of data collection, the more definite the frequency. Thus as the frequency component of an event's tendency to occur becomes less definite (which happens as the collection of events approaches one single occurrence within a given time frame), the observer's particular knowledge, characteristics, and relationship to the event become more and more relavent to the measurement or approximation of probability made, an approximation which was always subject to the knowledge of the individual observer.
Moving in the direction of longer time periods and larger datasets, with many repeatedly observed events, intersubjective assessments of both frequency and therefore probability, become more clear. The measurements made for frequency are objective in the sense that they really are true and meaningful from the observer's chosen reference timeframe and universe being observed, and they also tend to corroborate with other observers. This is objective frequency and could be considered "objective probability." But probability is, as I stated, referring to the _likelihood_ of this event occurring over a timeframe given, which becomes certain for events in the past that have been measured with certainty or that are guaranteed to happen in the future, and is subjective based on those which are approximated because they are yet to occur, or had to be inferred with error, or have been measured with error.
#ProbabilityTheory #HansHermannHoppe