Two events are equally unlikely if the probability that they do not happen is the same for each event. And, since the probability of an event happening and not happening must add to 1, equally unlikely events are also equally likely,
Equally likely events.
3/4
Two events that have the same chance of happening. For example, if I flip a coin the event of obtaining a 'head' is equally as likely as the event of obtaining a 'tail'. But equally likely does not mean 0.5 probability. It's possible that it's equally likely that someone in Ontario, Canada will die from being stung by a wasp as from being electrocuted in their kitchen at home. Neither event is very likely but the two events could be equally likely.
Relative frequency approximation is conducting experiments and counting the number of times the event occurs divided by the total number of events. The classical approach is determine the number of ways the event can occur divided by the total number of events.
Two events are equally unlikely if the probability that they do not happen is the same for each event. And, since the probability of an event happening and not happening must add to 1, equally unlikely events are also equally likely,
Equally likely events.
Nothing more significant than equally likely events.
3/4
The two events have the same probability of happening.
Two events that have the same chance of happening. For example, if I flip a coin the event of obtaining a 'head' is equally as likely as the event of obtaining a 'tail'. But equally likely does not mean 0.5 probability. It's possible that it's equally likely that someone in Ontario, Canada will die from being stung by a wasp as from being electrocuted in their kitchen at home. Neither event is very likely but the two events could be equally likely.
Relative frequency approximation is conducting experiments and counting the number of times the event occurs divided by the total number of events. The classical approach is determine the number of ways the event can occur divided by the total number of events.
Without more information all you can say is that they it is some non-negative number less than or equal to 0.5.
Subjective If you assume particular events will happen with a certain prior distribution, that is Bayesian probability.
I believe you mean to say, equally probable. By stating they are separate events, I assume that they are independent and that there is a single unique outcome to each event that can be identified. Ok, then the chance of each event or outcome is 1/10.
Well, that's not much of a question. Perhaps you are asking: What is the frequency interpretation of probability? This is called the classical interpretation of probability. Given n independent and identical trials with m occurrences of of a particular outcome, then the probability of this outcome, is equal to the limit of m/n as n goes to infinity. If you are asking: How can probabilities be estimated given data, based on frequency approach? A table is constructed, with intervals, and the number of events in each interval is calculated. The number of events divided by the total number of data is the relative frequency and an estimate of probability for the particular interval.
Independent events with a probability of zero