For borrowers with good credit scores, the mean debt for revolving and installment accounts is $15,015 (BusinessWeek, March 20, 2006). Assume the standard deviation is $3,730 and that debt amounts are normally distributed.

a. What is the probability that the debt for a randomly selected borrower with good credit is more than $18,000 (to 4 decimals)?


b. What is the probability that the debt for a randomly selected borrower with good credit is less than $10,000 (to 4 decimals)?


c.What is the probability that the debt for a randomly selected borrower with good credit is between $12,000 and $18,000 (to 4 decimals)?


d. What is the probability that the debt for a randomly selected borrower with good credit is no more than $14,000 (to 4 decimals)?

To solve these probability questions, we need to use the properties of the normal distribution. Specifically, we will use the z-score formula, which allows us to find the probability associated with a particular value from a normally distributed population.

The z-score formula is:

z = (X - μ) / σ

Where:
X is the value we're interested in (debt amount in this case)
μ is the mean of the population (given as $15,015)
σ is the standard deviation of the population (given as $3,730)

To find the probability using the z-score, we will use a standard normal distribution table or a calculator. Alternatively, we can use statistical software like Excel or Python.

a. To find the probability that the debt for a randomly selected borrower with good credit is more than $18,000, we need to find the z-score first:

z = (18,000 - 15,015) / 3,730 ≈ 0.7995

Using the standard normal distribution table or calculator, we find that the probability corresponding to a z-score of 0.7995 is approximately 0.7867. However, we need the probability of the debt being greater than $18,000, so we subtract this probability from 1:

P(X > 18,000) ≈ 1 - 0.7867 ≈ 0.2133

Therefore, the probability that the debt for a randomly selected borrower with good credit is more than $18,000 is approximately 0.2133.

b. To find the probability that the debt for a randomly selected borrower with good credit is less than $10,000, we follow the same process:

z = (10,000 - 15,015) / 3,730 ≈ -1.35

Using the standard normal distribution table or calculator, we find that the probability corresponding to a z-score of -1.35 is approximately 0.0885.

P(X < 10,000) ≈ 0.0885

Therefore, the probability that the debt for a randomly selected borrower with good credit is less than $10,000 is approximately 0.0885.

c. To find the probability that the debt for a randomly selected borrower with good credit is between $12,000 and $18,000, we need to find the individual probabilities for each bound and subtract them:

z1 = (12,000 - 15,015) / 3,730 ≈ -0.81
z2 = (18,000 - 15,015) / 3,730 ≈ 0.7995

Using the standard normal distribution table or calculator, we find that the probability corresponding to a z-score of -0.81 is approximately 0.2083, and the probability corresponding to a z-score of 0.7995 is approximately 0.7867.

P(12,000 < X < 18,000) ≈ 0.7867 - 0.2083 ≈ 0.5784

Therefore, the probability that the debt for a randomly selected borrower with good credit is between $12,000 and $18,000 is approximately 0.5784.

d. To find the probability that the debt for a randomly selected borrower with good credit is no more than $14,000, we can use the same approach:

z = (14,000 - 15,015) / 3,730 ≈ -0.273

Using the standard normal distribution table or calculator, we find that the probability corresponding to a z-score of -0.273 is approximately 0.3957.

P(X ≤ 14,000) ≈ 0.3957

Therefore, the probability that the debt for a randomly selected borrower with good credit is no more than $14,000 is approximately 0.3957.