Business Weekly conducted a survey of graduates from 30 top MBA programs. On the basis of the survey, assume the mean annual salary for graduates 10 years after graduation is $152,000. Assume the standard deviation is $45,000. Suppose you take a simple random sample of 48 graduates. Round all answers to four decimal places if necessary. a. What is the distribution of X? X - N( b. What is the distribution of ? N c. For a single randomly selected graduate, find the probability that her salary is between $142,257 and $147,705. d. For a simple random sample of 48 graduates, find the probability that the average salary is between $142,257 and $147,705. e. For part d), is the assumption of normal necessary? Yes No

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**Understanding Salary Distributions for MBA Graduates**

Business Weekly conducted a survey of graduates from 30 top MBA programs. Based on the survey, assume the mean annual salary for graduates 10 years after graduation is $152,000. Assume the standard deviation is $45,000. Suppose you take a simple random sample of 48 graduates. Round all answers to four decimal places if necessary.

**Questions and Answers:**

a. **What is the distribution of \( X \)?**
   \[
   X \sim N(152,000, 45000)
   \]

b. **What is the distribution of \( \overline{X} \)?**
   \[
   \overline{X} \sim N(152,000, \frac{45000}{\sqrt{48}})
   \]

c. **For a single randomly selected graduate, find the probability that her salary is between $142,257 and $147,705.**

d. **For a simple random sample of 48 graduates, find the probability that the average salary is between $142,257 and $147,705.**

e. **For part d), is the assumption of normal necessary?**
   \[
   \text{Yes}
   \]

In these questions:

1. \( X \) represents the salary of a single MBA graduate.
2. \( \overline{X} \) represents the average salary of a sample of 48 MBA graduates.
3. \( N(\mu, \sigma) \) represents a normal distribution with mean \( \mu \) and standard deviation \( \sigma \).

**Explanation of Formulas:**

1. **Distribution of \( X \)**:
   - \( X \) follows a normal distribution \( N \) with a mean \( \mu = \$152,000 \) and a standard deviation \( \sigma = \$45,000 \).

2. **Distribution of \( \overline{X} \)**:
   - The distribution of the sample mean \( \overline{X} \) also follows a normal distribution, but with a standard deviation adjusted by the square root of the sample size \( n = 48 \).

3. **Probability Calculations**:
   - The probabilities require using the properties of the normal distribution, typically by converting to the standard normal distribution (z-scores).

4. **Assumption of Normality**:
   - The assumption of normality is
Transcribed Image Text:**Understanding Salary Distributions for MBA Graduates** Business Weekly conducted a survey of graduates from 30 top MBA programs. Based on the survey, assume the mean annual salary for graduates 10 years after graduation is $152,000. Assume the standard deviation is $45,000. Suppose you take a simple random sample of 48 graduates. Round all answers to four decimal places if necessary. **Questions and Answers:** a. **What is the distribution of \( X \)?** \[ X \sim N(152,000, 45000) \] b. **What is the distribution of \( \overline{X} \)?** \[ \overline{X} \sim N(152,000, \frac{45000}{\sqrt{48}}) \] c. **For a single randomly selected graduate, find the probability that her salary is between $142,257 and $147,705.** d. **For a simple random sample of 48 graduates, find the probability that the average salary is between $142,257 and $147,705.** e. **For part d), is the assumption of normal necessary?** \[ \text{Yes} \] In these questions: 1. \( X \) represents the salary of a single MBA graduate. 2. \( \overline{X} \) represents the average salary of a sample of 48 MBA graduates. 3. \( N(\mu, \sigma) \) represents a normal distribution with mean \( \mu \) and standard deviation \( \sigma \). **Explanation of Formulas:** 1. **Distribution of \( X \)**: - \( X \) follows a normal distribution \( N \) with a mean \( \mu = \$152,000 \) and a standard deviation \( \sigma = \$45,000 \). 2. **Distribution of \( \overline{X} \)**: - The distribution of the sample mean \( \overline{X} \) also follows a normal distribution, but with a standard deviation adjusted by the square root of the sample size \( n = 48 \). 3. **Probability Calculations**: - The probabilities require using the properties of the normal distribution, typically by converting to the standard normal distribution (z-scores). 4. **Assumption of Normality**: - The assumption of normality is
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