QUESTION 17 In order to detect overfitting the researcher O should examine different samples of the data to see if that produces unstable results. O should note that an overfit model will have a low forecast error. will usually consult the Durbin-Watson statistic. O could use the t-statistics of the individual coefficients.QUESTION 18 A "training data set" is C used to compare models and pick the best one. used to build various models of interest. used to assess the performance of the normalization procedure. None of the options are correct.QUESTION 19 In data mining the model should be applied to a data set that was not used in the estimation process in order to find out the accuracy on unseen data; that "unseen" data set is called the training data set. the validation data set. the test data set. the holdout data set.QUESTION 20 With most data mining techniques we "partition" the data into "success" and "failure" results in order to create a target that is a dummy variable. only when we require a confusion matrix to be created. after estimating the appropriate technique. in order to judge how our model will do when we apply it to new data.QUESTION 14 Most economic time series are integrated of what order? zero one O two four