Calculate the residual standard error. Round your answer to two decimal places.

Question

BlackTom AI · Accepted Answer

The provided data for this question is incomplete for performing a numerical calculation.

Key information typically needed to compute the residual standard error (RSE) includes:
- The residuals (differences between observed values and fitted values) for each data point, or at least the sum of squared residuals (SSE).
- The number of observations (n).
- The number of estimated parameters in the model (k, including the intercept if present).

If you had SSE, the formula for the residual standard error is:
- RSE = sqrt(SSE / (n - k - 1))
This reflects the standard deviation of the residuals after accounting for the degrees of freedom used by the model.

Step-by-step approach if you have the necessary data:
1) Gather observed values y_i and corresponding fitted values ŷ_i from your model.
2) Compute residuals e_i = y_i - ŷ_i for each observation.
3) Sum the squared residuals: SSE = sum(e_i^2).
4) Determine n, the total number of observations, and k, the number of parameters estimated in the model (including the intercept if one is used).
5) Compute the degrees of freedom: df = n - k - 1.
6) Calculate RSE = sqrt(SSE / df).
7) Round the result to two decimal places, as required.

Because the answer options are not provided in the prompt (the answer_options field is empty), there is no specific choice to evaluate or compare. If you can share the dataset values, the fitted values, or the SSE along with n and k, I can carry out the calculation and produce the rounded numeric result.

Alternatively, if this is from a particular regression output (e.g., a summary in R, Python, or a statistical package), you can locate the residual standard error directly in the model summary section under residuals or model diagnostics, which typically reports RSE along with degrees of freedom.

BUSI_V 291 202 2024W2 Sample Midterm Exam (Canvas)

Calculate the residual standard error. Round your answer to two decimal places.

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