The probability you're referring to is known as the "posterior" probability. This is the updated probability of an event occurring after taking into consideration new information. Here are the steps:

1. Start with a "prior" probability: This is your initial estimate of the probability of an event before new data is taken into account.

2. Collect new information: This could be new data, observations, or evidence that is relevant to the event you're trying to predict.

3. Update the prior probability: Using Bayes' theorem, you can update your prior probability based on the new information. Bayes' theorem combines the effect of the new information with the prior probability to give a new, updated probability.

4. The result is the "posterior" probability: This is your updated estimate of the probability of the event after taking into account the new information.

Question

The probability you're referring to is known as the "posterior" probability. This is the updated probability of an event occurring after taking into consideration new information. Here are the steps:

1. Start with a "prior" probability: This is your initial estimate of the probability of an event before new data is taken into account.

2. Collect new information: This could be new data, observations, or evidence that is relevant to the event you're trying to predict.

3. Update the prior probability: Using Bayes' theorem, you can update your prior probability based on the new information. Bayes' theorem combines the effect of the new information with the prior probability to give a new, updated probability.

4. The result is the "posterior" probability: This is your updated estimate of the probability of the event after taking into account the new information.

Knowee AI · Accepted Answer

The probability you're referring to is known as the "posterior" probability. This is the updated probability of an event occurring after taking into consideration new information. Here are the steps:

1. Start with a "prior" probability: This is your initial estimate of the probability of an event before new data is taken into account.

2. Collect new information: This could be new data, observations, or evidence that is relevant to the event you're trying to predict.

3. Update the prior probability: Using Bayes' theorem, you can update your prior probability based on the new information. Bayes' theorem combines the effect of the new information with the prior probability to give a new, updated probability.

4. The result is the "posterior" probability: This is your updated estimate of the probability of the event after taking into account the new information.

On the basis of new information, we update the prior probability to arrive at a conditional probability called a '' probability.

Question

On the basis of new information, we update the prior probability to arrive at a conditional probability called a '' probability.

Solution

Similar Questions

Upgrade your grade with Knowee