Question 1163400
To calculate the standard error of the estimate ($S_e$) for a multiple regression model, we use the sum of squared errors ($SSE$) and the degrees of freedom associated with the error.

### 1. Identify the Given Information
* **Sample size ($n$):** $29$
* **Number of independent variables ($k$):** $2$ (Poverty rate and Median income)
* **Sum of Squared Errors ($SSE$):** $4,136,781$
* **Total Sum of Squares ($SST$):** $7,662,937$ (Note: $SST$ is not required for this specific calculation)

### 2. The Formula
The standard error of the estimate is the square root of the mean square error ($MSE$):
$$S_e = \sqrt{\frac{SSE}{n - k - 1}}$$

Where:
* $n - k - 1$ represents the degrees of freedom for the error ($df_E$).

### 3. Calculation
**Step 1: Calculate the degrees of freedom ($df_E$)**
$$df_E = 29 - 2 - 1 = 26$$

**Step 2: Calculate the Mean Square Error ($MSE$)**
$$MSE = \frac{4,136,781}{26} \approx 159,106.9615$$

**Step 3: Calculate the square root**
$$S_e = \sqrt{159,106.9615} \approx 398.8821$$

### Final Answer
The standard error of the estimate is approximately **$398.88$**.