Answer:
Null Hypothesis: No first order autocorrelation
Alternative hypothesis: first order correlation exists
The assumptions to run this test are:
1) Errors are normally distributed with mean 0
2) Errors follows an stationary process
3) Independence condition between the erros
The statistic is defined as:
[tex] DW = \frac{\sum_{t=2}^ T (e_t -e_{t-1})^2}{\sum_{t=1}^T e^2_t}[/tex]
And if the value for the DW is near to 0 we can conclude that the assumption of Independence is not satisfied.
Step-by-step explanation:
The Durbin Watson test is a way to check autocorrelation in residuals for a time seeries or a regression.
We need to remember that the autocorrelation is the similarity of the time series in successive intervals. When we conduct this type of test we are checking if the time series can be modeled with and AR(1) process autoregressive.
The system of hypothesis on this case are:
Null Hypothesis: No first order autocorrelation
Alternative hypothesis: First order correlation exists
The assumptions to run this test are:
1) Errors are normally distributed with mean 0
2) Errors follows an stationary process
3) Independence condition between the errors
The statistic is defined as:
[tex] DW = \frac{\sum_{t=2}^ T (e_t -e_{t-1})^2}{\sum_{t=1}^T e^2_t}[/tex]
And if the value for the DW is near to 0 we can conclude that the assumption of Independence is not satisfied.