What is the probability of a customer only insuring one non-sports car?

In summary: Answer: In summary, the probability that a randomly selected customer insures exactly one car and that car is not a sports car is 0.205 or 20.5%. This can be calculated by using the given information and creating a Venn diagram to visualize the relationships between the different probabilities.
  • #1
Jason123
3
0
Need help with a probability problem. I have the answer from the answer key, I just don't know how to figure it out.An insurance company examines its pool of auto insurance customers and gathers the following information:1) All customers insure at least one car.

2) 70% of the customers insure more than one car.

3) 20% of customers insure a sports car.

4) Of those customers who insure more than one car, 15% insure a sports car.
Calculate the probability that a randomly selected customer insures exactly one car and that car is not a sports car.
 
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  • #2
Hello Jason123 and welcome to MHB! :D

Any thoughts on where to begin?

Also, we ask that users do not post duplicate topics, thanks. I've deleted your other thread.
 
  • #3
I know I need to use the formula, pr(AnB)/Pr(B). For this problem I believe that pr(AnB) = the probability that someone has only one car and the car is not a sports car. And then divide that by the probability that someone has only one car. but I can't seem to get those numbers. Answer key says its .205.
 
  • #4
Here's how I would do this problem (I'm not big on memorizing formulas):
"An insurance company examines its pool of auto insurance customers and gathers the following information:"
Imagine 1000 customers.

"1) All customers insure at least one car.

2) 70% of the customers insure more than one car."
So 700 insure more than one car, 300 insure one car.

"3) 20% of customers insure a sports car."
So 200 insure a sports car.

"4) Of those customers who insure more than one car, 15% insure a sports car."
Of the 700 customers who insure more than one car, .15(700)= 105 insure a sports car. Since 200 customers insured a sports car, that means there are 200- 105= 95 customers who insure only one car and that is a sports car. Since 300 customers insure one car, 300- 95= 205 customers insure one car and that car is not a sports car.

"Calculate the probability that a randomly selected customer insures exactly one car and that car is not a sports car."
That's easy now. Out of 1000 customers, 205 of them insure one car which is not a sports car. The probability is 205/1000= 0.205 or 20.5%.
 
  • #5
Consider the following Venn diagram:

View attachment 6082

We must have:

\(\displaystyle x+0.7+0.095=1\)

\(\displaystyle x=0.205\)
 

Attachments

  • insurancevenn.png
    insurancevenn.png
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FAQ: What is the probability of a customer only insuring one non-sports car?

What is conditional probability?

Conditional probability is a mathematical concept that measures the likelihood of an event occurring given that another event has already occurred. It is represented by P(A|B), where A and B are events and P(A|B) is the probability of event A happening, assuming that event B has already occurred.

How is conditional probability calculated?

Conditional probability is calculated by dividing the probability of the intersection of event A and B (P(A∩B)) by the probability of event B (P(B)). This can also be represented as P(A|B) = P(A∩B) / P(B).

What is the difference between conditional probability and joint probability?

Conditional probability and joint probability both involve the probability of two events occurring. However, conditional probability takes into account that one event has already occurred, whereas joint probability does not. Conditional probability is calculated as P(A|B), while joint probability is calculated as P(A∩B).

How is conditional probability used in real life?

Conditional probability has numerous applications in real life, particularly in fields such as statistics, finance, and machine learning. It can be used to predict the likelihood of outcomes, assess risk, and make informed decisions based on available data. For example, conditional probability can be used to calculate the probability of a medical test being accurate, given a patient's symptoms.

What are some common misconceptions about conditional probability?

One common misconception about conditional probability is that it is the same as causation. This is not true, as conditional probability only measures the likelihood of one event occurring given that another event has occurred, and does not imply a causal relationship. Another misconception is that conditional probability always results in a smaller probability, when in fact it can sometimes result in a larger probability if the events are not independent.

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