This is not the place to discuss personal or speculative theories. If you post your theory, it will likely be deleted.Larry Lacey said:Thanks for the feedback mathman. For me to do this, it would be best for me to present this as a pdf file, ie as an attachment. Will that be OK? Don't want to be presumptive.
Here's the relevant rule:Larry Lacey said:It's not a theory PeroK. It is a framework constructed using statistical theory. It could be flawed but that is for others to argue based on statistical theory. However, I will not post it until I get an OK to do so, as I'm new to the forum and ts rules.
OP tried posting his paper anyway, and it has indeed been deleted. Thread is closed.PeroK said:This is not the place to discuss personal or speculative theories. If you post your theory, it will likely be deleted.
Probability is a measure of the likelihood that a certain event will occur. It is typically expressed as a number between 0 and 1, where 0 indicates impossibility and 1 indicates certainty.
Entropy is a measure of the amount of disorder or randomness in a system. In a probability context, entropy can be thought of as the uncertainty or unpredictability of an event occurring. As the probability of an event decreases, the entropy increases.
An exponentially increasing sample space refers to a situation where the number of possible outcomes in a sample space increases at an exponential rate. This often occurs in situations where there are multiple independent events with a large number of possible outcomes.
To calculate the probability of an event in an exponentially increasing sample space, you would divide the number of desired outcomes by the total number of possible outcomes. This is known as the classical probability formula.
In an exponentially increasing sample space, as the sample size increases, the probability of a specific event occurring decreases. This is because as the sample size increases, the number of possible outcomes also increases, making it less likely for a specific event to occur.