Geometric and binomial probability #3 and #4 According to a 2019 Kaiser Family Foundation analysis, it is estimated that approximately 27%of U.S. adults under the age of 65 (about 54 million) have pre-existing health conditions thatwould likely have made them uninsurable in the individual markets that existed in most statesbefore the Affordable Care Act.Suppose we randomly select U.S. adults under 65.1. What is the probability that the tenth adult selected is the first adult with a pre-existinghealth condition?2. If we randomly select a group of 20 adults for a study on health care, what is theprobability that we select 12 of them with a pre-existing health condition? Sketch orpaste the binomial distribution for this scenario.3. If we randomly select a group of 50 adults for a different study, what is the probabilitythat we select at least half of them with a pre-existing health condition?4. According to the US census, there are approximately 29,305 adults under the age of 65 in Sacramento. How many ofthose adults do we expect to have a pre-existing health condition that will make them uninsurable?

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Description: Geometric and binomial probability #3 and #4 According to a 2019 Kaiser Family Foundation analysis, it is estimated that approximately 27%of U.S. adults under the age of 65 (about 54 million) have pre-existing health conditions thatwould likely have

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Geometric and binomial probability #3 and #4

MATLAB: An Introduction with Applications

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Publisher:Amos Gilat

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Concept explainers

Contingency Table

A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.

Binomial Distribution

Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.

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Geometric and binomial probability

#3 and #4

According to a 2019 Kaiser Family Foundation analysis, it is estimated that approximately 27%
of U.S. adults under the age of 65 (about 54 million) have pre-existing health conditions that
would likely have made them uninsurable in the individual markets that existed in most states
before the Affordable Care Act.
Suppose we randomly select U.S. adults under 65.
1. What is the probability that the tenth adult selected is the first adult with a pre-existing
health condition?
2. If we randomly select a group of 20 adults for a study on health care, what is the
probability that we select 12 of them with a pre-existing health condition? Sketch or
paste the binomial distribution for this scenario.
3. If we randomly select a group of 50 adults for a different study, what is the probability
that we select at least half of them with a pre-existing health condition?
4. According to the US census, there are approximately 29,305 adults under the age of 65 in Sacramento. How many of
those adults do we expect to have a pre-existing health condition that will make them uninsurable?

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