A discrete probability distribution does what?

A discrete probability distribution does what?

• A. Lists continuous ranges of outcome probabilities
• B. Lists each possible value of a random variable
• C. Ignores the probabilities of infinite outcomes
• D. Represents probabilities in a graphical format only

Answer: (B)

A discrete probability distribution specifically focuses on a finite or countably infinite set of outcomes for a random variable. It lists each possible value of that random variable and assigns a corresponding probability to each value, ensuring that the sum of all probabilities equals one. This characteristic allows for precise calculations and analyses in scenarios where outcomes can be distinctly identified, such as the roll of a die or the number of heads in a series of coin tosses. In contrast, other choices do not accurately capture the essence of a discrete probability distribution. For example, a distribution listing continuous ranges of outcomes applies to continuous probability distributions, not discrete ones. Additionally, neglecting infinite outcomes pertains more to the nature of discrete distributions when they are limited compared to continuous distributions. Lastly, while graphical representations can be used to illustrate probability distributions, this is not a defining feature of what a discrete probability distribution does; the primary focus is on listing values and their associated probabilities.

A discrete probability distribution specifically focuses on a finite or countably infinite set of outcomes for a random variable. It lists each possible value of that random variable and assigns a corresponding probability to each value, ensuring that the sum of all probabilities equals one. This characteristic allows for precise calculations and analyses in scenarios where outcomes can be distinctly identified, such as the roll of a die or the number of heads in a series of coin tosses.

In contrast, other choices do not accurately capture the essence of a discrete probability distribution. For example, a distribution listing continuous ranges of outcomes applies to continuous probability distributions, not discrete ones. Additionally, neglecting infinite outcomes pertains more to the nature of discrete distributions when they are limited compared to continuous distributions. Lastly, while graphical representations can be used to illustrate probability distributions, this is not a defining feature of what a discrete probability distribution does; the primary focus is on listing values and their associated probabilities.