A prospective MBA student would like to examine the factors that impact starting salary upon graduation and decides to develop a model that uses program per-year tuition as a predictor of starting salary. Data were collected for 37 full-time MBA programs offered at private universities. The results are displayed in the accompanying table, and the regression equation and other values are provided. Use this information to complete parts (a) through (c) below. Y = -12,195.7+2.4032X, n n n Σ Υ = 4,230,133, Σ γ = 520,438,426,235, Σ XY; = 234,279,400,152 i=1 i=1 i=1 Click the icon to view the data table. OD. It measures the variability in the actual per-year tuition from the predicted number of starting salary. b. Determine the standard error of the estimate. Syx = (Round to two decimal places as needed.) c. How useful do you think this regression model is for predicting starting salary? Since the value of r² IS the regression model is for predicting starting salary.

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A prospective MBA student would like to examine the factors that impact starting salary upon graduation and decides to develop a model that uses program per-year tuition as a predictor of starting salary. Data were collected for 37 full-time MBA programs offered at private universities. The results are displayed in the accompanying table, and the regression equation and other values are provided. Use this information to complete parts (a) through (c) below.

\[ \hat{Y}_i = -12,195.7 + 2.4032X_i \]

\[
\sum_{i=1}^{n} Y_i = 4,230,133,
\quad \sum_{i=1}^{n} Y_i^2 = 520,438,426,235,
\quad \sum_{i=1}^{n} X_i Y_i = 234,279,400,152
\]

- Click the icon to view the data table.

**Tasks:**

**a.** Determine the variability in the actual per-year tuition from the predicted number of starting salary.

**b.** Determine the standard error of the estimate.
\[ S_{YX} = \, \_\_\_ \]
(Round to two decimal places as needed.)

**c.** How useful do you think this regression model is for predicting starting salary?

Since the value of \( r^2 \) is \[ \_\_\_\_ \]
the regression model is \[ \_\_\_\_ \] for predicting starting salary.
Transcribed Image Text:A prospective MBA student would like to examine the factors that impact starting salary upon graduation and decides to develop a model that uses program per-year tuition as a predictor of starting salary. Data were collected for 37 full-time MBA programs offered at private universities. The results are displayed in the accompanying table, and the regression equation and other values are provided. Use this information to complete parts (a) through (c) below. \[ \hat{Y}_i = -12,195.7 + 2.4032X_i \] \[ \sum_{i=1}^{n} Y_i = 4,230,133, \quad \sum_{i=1}^{n} Y_i^2 = 520,438,426,235, \quad \sum_{i=1}^{n} X_i Y_i = 234,279,400,152 \] - Click the icon to view the data table. **Tasks:** **a.** Determine the variability in the actual per-year tuition from the predicted number of starting salary. **b.** Determine the standard error of the estimate. \[ S_{YX} = \, \_\_\_ \] (Round to two decimal places as needed.) **c.** How useful do you think this regression model is for predicting starting salary? Since the value of \( r^2 \) is \[ \_\_\_\_ \] the regression model is \[ \_\_\_\_ \] for predicting starting salary.
This table provides a detailed comparison of program tuition costs per year with the mean starting salary upon graduation. The table aims to assist prospective students in evaluating the potential return on investment for various educational programs.

### Table Description:

- **Column A: Program Per-Year Tuition ($)**
  - Provides the annual tuition cost for different programs.
  - Tuition fees range from $39,553 to $66,187.

- **Column B: Mean Starting Salary Upon Graduation ($)**
  - Displays the average starting salary that graduates earn upon completing their respective programs.
  - Starting salaries vary from $54,719 to $151,351.

### Data Insights:

1. **Highest Tuition and Salary:**
   - The highest program tuition is $66,187 with a mean starting salary of $152,400.

2. **Lowest Tuition and Salary:**
   - The lowest program tuition is $39,553 with a mean starting salary of $54,719.

3. **Potential Return on Investment:**
   - Programs with higher tuition tend to correspond with higher starting salaries, indicating a potential link between the investment in education and initial career earnings.

4. **Variation in Cost vs. Income:**
   - There is significant variation in both tuition costs and starting salaries, highlighting the need for careful consideration when selecting a program.

This information serves as a valuable resource for students assessing the financial implications and benefits of their educational choices.
Transcribed Image Text:This table provides a detailed comparison of program tuition costs per year with the mean starting salary upon graduation. The table aims to assist prospective students in evaluating the potential return on investment for various educational programs. ### Table Description: - **Column A: Program Per-Year Tuition ($)** - Provides the annual tuition cost for different programs. - Tuition fees range from $39,553 to $66,187. - **Column B: Mean Starting Salary Upon Graduation ($)** - Displays the average starting salary that graduates earn upon completing their respective programs. - Starting salaries vary from $54,719 to $151,351. ### Data Insights: 1. **Highest Tuition and Salary:** - The highest program tuition is $66,187 with a mean starting salary of $152,400. 2. **Lowest Tuition and Salary:** - The lowest program tuition is $39,553 with a mean starting salary of $54,719. 3. **Potential Return on Investment:** - Programs with higher tuition tend to correspond with higher starting salaries, indicating a potential link between the investment in education and initial career earnings. 4. **Variation in Cost vs. Income:** - There is significant variation in both tuition costs and starting salaries, highlighting the need for careful consideration when selecting a program. This information serves as a valuable resource for students assessing the financial implications and benefits of their educational choices.
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