Simple Dependent Independent Events

Assume the events A and B are independent events. If P(A and B) = 0.25 and P(A) = 0.4, what is P(B)?

• 0.65

• 0.625

• 0.15

• 1.6

Given that P(A) = 0.54 and P(B) = 0.21 and P(A and B) = 0.15, determine if the events A and B are independent.

• Yes. (0.54)(0.21) does not equal 0.15 which means the events A and B are independent.

• Yes, P(A and B) is not zero so the events must be independent.

• No. P(A and B) = 0.15 which is not zero so the events are not independent.

• No. (0.54)(0.21) = (0.1134) which does not equal the stated value of P(A and B) which means A and B are not independent.

A letter of the alphabet is chosen at random, then a coin is flipped. What is the probability of choosing a letter from the word MATH then getting tails? 

• 4/26 + 1/2

• 4/26 x 1/2

• 4/25 x 1/2

• 4/25 + 1/2

If the outcome of one event does not affect the outcome of the other event, the events are ________?

• Dependent Events

• Independent Events

• Simple Events

• Complementary Events

If an event has one outcome or a collection of outcomes, the event is a(n) ______.

• Simple Event

• Tree Diagram

• Sample Space

• Experimental Event

if the outcome of the first event affects the outcome of the second event, then that is a(n) _______________ .

• Independent Event

• Dependent Event

• Complimentary Event

• Tree Diagram

The likelihood that a single, specific event will occur is called - 

• sample space

• compound probability

• a complement

• simple probability

Which of the following expressions would be used to calculate the complement of an event occurring?

• P(event) - 1

• P(event 1) x    P(event 2)

• P(event)/possible outcomes

• 1 - P(event)

Which of the following expressions can be used to calculate the probability of two related events occurring?

• P(event) x 2

• P(event 1) +   P(event 2)

• P(event 1) x     P(event 2)

• P(event 1 + 2)

In compound probability, if one event does not affect the other event or events, it is referred to as - 

• theoretical probability

• independent probability

• experimental probability

• dependent probability