For a combination of α (level of significance) = 0.05, n (sample size) = 25, k (number of independent variables in the model) = 1 and D (Durbin-Watson statistic) = 2.60 , what statistical decision should be made when testing the null hypothesis of no positive autocorrelation? a. Accept the null hypothesis. b. Do not reject the null hypothesis. c. Accept the alternative hypothesis. d. Neither reject nor not reject the null hypothesis.

The Durbin-Watson statistic is a test statistic used to detect the presence of autocorrelation (a relationship between values separated from each other by a given time lag) in the residuals (prediction errors) from a regression analysis.

The Durbin-Watson statistic ranges from 0 to 4, and a value around 2 suggests that there is no autocorrelation. In this case, the Durbin-Watson statistic is 2.60, which is slightly above 2, suggesting a negative autocorrelation.

However, the decision to reject or not reject the null hypothesis of no positive autocorrelation does not solely depend on the value of the Durbin-Watson statistic. It also depends on the critical value of the Durbin-Watson statistic for a given level of significance (α), number of observations (n), and number of predictors (k).

The critical values for the Durbin-Watson statistic can be found in statistical tables, but they are not provided here. Therefore, without the critical values, we cannot make a definitive statistical decision.

So, the answer is:

d. Neither reject nor not reject the null hypothesis.