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According to a survey, the mean student loan at graduation is $45,000. suppose that student loans are normally distributed with a standard deviation of $4,000. a graduate with a student loan is selected at random. find the following probabilities. (round your answers to four decimal places.)

(a) the loan is greater than $49,000
(b) the loan is less than $43,000
(c) the loan falls between $41,000 and $50,200

1 Answer

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Final answer:

The probability that the loan is greater than $49,000 is 0.1587. The probability that the loan is less than $43,000 is 0.3085. The probability that the loan falls between $41,000 and $50,200 is 0.7445.

Step-by-step explanation:

(a) The loan is greater than $49,000:

To find this probability, we need to calculate the z-score and then find the area under the normal curve to the right of the z-score.

First, we calculate the z-score using the formula:

z = (x - mean) / standard deviation

Plugging in the values, we have:

z = (49000 - 45000) / 4000 = 1

Next, we look up the area to the right of z = 1 in the standard normal distribution table. The area is 0.1587.

Therefore, the probability that the loan is greater than $49,000 is 0.1587.

(b) The loan is less than $43,000:

To find this probability, we again calculate the z-score:

z = (43000 - 45000) / 4000 = -0.5

Then, we look up the area to the left of z = -0.5 in the standard normal distribution table. The area is 0.3085.

Therefore, the probability that the loan is less than $43,000 is 0.3085.

(c) The loan falls between $41,000 and $50,200:

To find this probability, we calculate the z-scores for both values:

z1 = (41000 - 45000) / 4000 = -1

z2 = (50200 - 45000) / 4000 = 1.3

Next, we find the area to the left of z = -1 and to the left of z = 1.3 in the standard normal distribution table. The areas are 0.1587 and 0.9032, respectively.

To find the area between these two z-scores, we subtract the area to the left of z = -1 from the area to the left of z = 1.3:

Area = 0.9032 - 0.1587 = 0.7445.

Therefore, the probability that the loan falls between $41,000 and $50,200 is 0.7445.

User Rakesh Kasinathan
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