Describe the Difference Between Discrete and Continuous Probability Distributions

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The Answer is Discrete and continuous probability distributions are two different types of distributions used to represent the likelihood of different outcomes in a given situation.

Discrete probability distributions are used when the outcomes are distinct and separate, such as the number of heads when flipping a coin or the number of cars passing through a toll booth in a given time period. In a discrete distribution, the probabilities are assigned to specific values or intervals, and the sum of all probabilities equals 1.

On the other hand, continuous probability distributions are used when the outcomes are continuous and can take any value within a certain range, such as the height of individuals in a population or the time it takes for a machine to fail. In a continuous distribution, the probabilities are assigned to intervals or ranges of values, and the area under the probability density function equals 1.

The main difference in how they compute probabilities for certain outcomes lies in the methods used to calculate them. In a discrete distribution, probabilities are calculated by counting the number of favorable outcomes and dividing by the total number of possible outcomes. In a continuous distribution, probabilities are calculated by finding the area under the probability density function within a given interval.

In summary, discrete probability distributions are used for distinct and separate outcomes, while continuous probability distributions are used for continuous and infinite outcomes. The methods for computing probabilities for certain outcomes differ based on the nature of the distribution.

Describe the Difference Between Discrete and Continuous Probability Distributions

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