Probability question on bank customers

In summary, the probability of a customer arriving in a bank per minute is 0.9, which means that there is a 90% chance of a customer arriving in the first minute. This probability does not change for subsequent minutes, so in 10 minutes, the expected number of customers would be 9. This is due to the property of independence, where the outcome of one event does not affect the outcome of another event. Therefore, the answer is determined by simply multiplying the probability by the number of minutes.
  • #1
aaa59
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The probability of a customer arriving in a bank per minute is 0.9. How many customers will arrive in 10 minutes?

Thanks
Ashish
 
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  • #2
What are your thoughts on how to approach this question? Does the probability of a customer arriving in the first minute affect the probability of a customer arriving in the second minute? What is this property called, and how does it help guide you to the answer here?
 
  • #3
I have absolutely no idea
 
  • #4
I would say that in 1 minute there is a 90% chance that a customer may arrive, so in 10 minutes the number of customers I would expect is 9.
 
  • #5
Correct. On average...
 
  • #6
thanks
 
  • #7
Think about what a probability is. Then think about how the probability of 0.9 was determined. At that point the answer is obvious.
 

1. What is the likelihood of a bank customer defaulting on their loan?

The likelihood of a bank customer defaulting on their loan depends on various factors such as their credit score, income, and past financial history. It is impossible to give a definite answer without knowing these individual factors.

2. How does the bank calculate the probability of a customer defaulting?

Banks use complex mathematical models to estimate the probability of a customer defaulting. These models take into account various factors such as credit score, income, and past financial history.

3. Can the probability of a customer defaulting be accurately predicted?

While banks use advanced models to calculate the probability of default, it is impossible to accurately predict the behavior of individual customers. These models can only provide an estimate based on historical data and trends.

4. What is the impact of probability on a bank's lending decisions?

The probability of a customer defaulting is one of the key factors that banks consider when making lending decisions. A higher probability of default may result in the bank offering a higher interest rate or rejecting the loan application altogether.

5. How can banks reduce their risk in lending to customers with a high probability of default?

Banks can manage their risk by diversifying their loan portfolio, setting stricter lending criteria, and closely monitoring the financial health of their customers. They may also require collateral or a co-signer for loans with a high probability of default.

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