Constructing Probability Distributions for Random Variables

What does the random variable X represent in the context of the experiment?

• The number of heads obtained

• The number of tails obtained

• The total number of coin flips

• The probability of getting a head

How many possible outcomes are there when flipping a fair coin three times?

• 12

• 3

• 8

• 6

What is the probability of getting exactly one head in three coin flips?

• 2/3

• 1/2

• 3/8

• 1/8

Tags

CCSS.HSS.MD.B.6

CCSS.HSS.MD.B.7

How many outcomes result in getting no heads at all?

• 1

• 2

• 3

• 4

What is the probability of getting exactly two heads in three coin flips?

• 3/4

• 1/2

• 3/8

• 1/4

Tags

CCSS.HSS.MD.B.6

CCSS.HSS.MD.B.7

What is the highest number of heads one can get in this experiment?

• 1

• 4

• 2

• 3

Tags

CCSS.7.SP.C.8C

Which probability value is shared by getting exactly one head and getting exactly two heads?

• 1/8

• 1/4

• 3/8

• 1/2

What kind of probability distribution is constructed in the video?

• Continuous probability distribution

• Discrete probability distribution

• Binomial distribution

• Normal distribution

Tags

CCSS.HSS.MD.A.3

CCSS.HSS.MD.A.4

What is the total probability of all possible outcomes?

• 1/2

• 1

• 3/4

• 7/8

Tags

CCSS.7.SP.C.5

Why can't the random variable X take on values like half or pi?

• Because it's a continuous variable

• Because it's a discrete variable

• Due to the nature of the coin

• Because of the limitations of probability theory