Understanding Valid Probability Models

The video tutorial examines the validity of three probability models. Model A is valid as its probabilities are between 0 and 1 and sum to 1. Model B is invalid due to a negative probability. Model C is invalid because its probabilities do not sum to 1.

What is the first requirement for a set of probabilities to be considered a valid probability model?

• All probabilities must be equal to 0.

• All probabilities must be between 0 and 1.

• All probabilities must be less than 0.

• All probabilities must be greater than 1.

What is the second requirement for a probability model to be valid?

• Probabilities must add up to 0.

• Probabilities must add up to 1.

• Probabilities must add up to 2.

• Probabilities must add up to 0.5.

Why is the first probability model considered valid?

• Probabilities are less than 0.

• Probabilities are between 0 and 1 and add up to 1.

• Probabilities are greater than 1.

• All probabilities are negative.

What makes the second probability model invalid?

• Probabilities add up to more than 1.

• One probability is negative.

• All probabilities are zero.

• One probability is greater than 1.

In the second model, what is the issue with having a negative probability?

• It makes the model valid.

• It has no effect on the model's validity.

• It is acceptable in probability models.

• It invalidates the probability model.

What is the main issue with the third probability model?

• Probabilities add up to 0.99 instead of 1.

• Probabilities add up to 2.

• Probabilities are negative.

• All probabilities are greater than 1.

Why is it important for probabilities to add up to 1 in a valid model?

• To ensure the total probability represents a complete set of outcomes.

• To ensure probabilities are greater than 1.

• To ensure all outcomes are equally likely.

• To ensure probabilities are negative.

What happens if the probabilities in a model add up to less than 1?

• The model is still valid.

• The model is invalid because it doesn't represent a complete set of outcomes.

• The model is valid if all probabilities are positive.

• The model is valid if all probabilities are negative.

Which of the following is NOT a requirement for a valid probability model?

• Probabilities must add up to 1.

• Probabilities must be negative.

• Probabilities must represent a complete set of outcomes.

• Probabilities must be between 0 and 1.

If a probability model has a probability greater than 1, what does this indicate?

• The model is complete.

• The model is invalid.

• The model is valid.

• The model is partially valid.