Question

What is the difference between independent and conditional probability? Which one requires the use of the Addition Rule?Explain.

Answer 1

Answer:

In probability, independent events are those that if one event occurs, it does not change the probability of the other event.

Whereas conditional probability is defined as the probability of one event occurring with some relationship to one or more other events.

The addition rule is used for both the independent and conditional probabilities.

For independent event the probability is shown as :

$P(YorZ)=P(Y)+P(Z)$

For conditional: $P(YorZ)=P(Y)+P(Z)-P(YandZ)$

Answer 2

Independent probability means that the test subjects do not affect one another. One's event occurring does not affect the other.

Conditional probability means that an event happening only happened because another even had already occurred.

The addition rule i believe is a Conditional probability

hope this helps