Probability - Addition Rule

Front

What is the Addition Rule in probability?

Back

The Addition Rule states that the probability of the occurrence of at least one of two events A or B is given by P(A or B) = P(A) + P(B) - P(A and B).

Front

If there are 6 puppies, 4 gerbils, and 7 parakeets in a pet store, what is the total number of pets?

Back

Total pets = 6 (puppies) + 4 (gerbils) + 7 (parakeets) = 17 pets.

Front

What is the probability of choosing a puppy or a parakeet from a pet store with 6 puppies, 4 gerbils, and 7 parakeets?

Back

P(puppy or parakeet) = (Number of puppies + Number of parakeets) / Total pets = (6 + 7) / 17 = 13/17.

Front

What is the probability of a person driving while intoxicated or having a car accident if P(accident) = 0.09, P(intoxicated) = 0.32, and P(accident and intoxicated) = 0.15?

Back

P(intoxicated or accident) = P(intoxicated) + P(accident) - P(accident and intoxicated) = 0.32 + 0.09 - 0.15 = 0.26.

Front

If the probability of owning a skateboard is 0.37 and owning a bicycle is 0.81, with both being 0.36, what is the probability of owning either?

Back

P(skateboard or bicycle) = P(skateboard) + P(bicycle) - P(both) = 0.37 + 0.81 - 0.36 = 0.82.

Front

In a jar with 1 red, 3 green, 2 blue, and 4 yellow marbles, what is the probability of choosing a yellow or green marble?

Back

P(yellow or green) = (Number of yellow + Number of green) / Total marbles = (4 + 3) / 10 = 7/10.

Front

What is the probability of choosing a 5 or an even number from numbers 1 to 10?

Back

Even numbers are 2, 4, 6, 8, 10 (5 total). P(5 or even) = (1 + 5) / 10 = 6/10 = 3/5.

Front

Define mutually exclusive events in probability.

Back

Mutually exclusive events are events that cannot occur at the same time. For example, rolling a 3 or a 5 on a single die.

Front

What is the complement of an event in probability?

Back

The complement of an event A, denoted as A', is the event that A does not occur. P(A) + P(A') = 1.

Front

How do you calculate the probability of independent events?

Back

For independent events A and B, P(A and B) = P(A) * P(B).