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The question shown in the image asks about the Durbin-Watson statistic and which of the following options is correct regarding autocorrelation detection.

The correct answer is:

**"Tomará un valor próximo a dos cuando no exista autocorrelación."**  
(English: "It will take a value close to two when there is no autocorrelation.")

Explanation:
- The **Durbin-Watson statistic** is used in regression analysis to detect the presence of autocorrelation in the residuals (errors) of a model. A value close to 2 suggests that there is no autocorrelation. Values significantly below 2 indicate positive autocorrelation, while values above 2 indicate negative autocorrelation.

Would you like more details on how the Durbin-Watson statistic works?

Here are 5 related questions to expand your understanding:
1. What is the significance of positive and negative autocorrelation?
2. How can autocorrelation affect the results of a regression model?
3. What are alternative methods for detecting autocorrelation besides Durbin-Watson?
4. How can autocorrelation be corrected in a time series model?
5. What is the difference between autocorrelation and partial autocorrelation?

**Tip:** Autocorrelation often occurs in time series data when the observations are dependent on their previous values.

En relación con la detección de la autocorrelación. ¿Cuál de las siguientes opciones es correcta acerca del estadístico Durbin y Watson?

Understand how the Durbin-Watson statistic detects autocorrelation in regression models. A value close to 2 indicates no autocorrelation. This guide covers key concepts, formulas, and explanations, suitable for college-level statistics and econometrics courses.

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