A process, xt, which has a constant mean and variance, and zero autocovariance for all non-zero lags is best described as:

If a residual series is negatively autocorrelated, which one of the following is the most likely value of the Durbin Watson statistic?

A normal distribution has coefficients of skewness and excess kurtosis which are respectively:

What would be the consequences for the OLS estimator if autocorrelation is present in a regression model but ignored?

If the residuals of a model containing lags of the dependent variable are autocorrelated, which one of the following could this lead to?

Consider a series that follows an MA(1) with zero mean and a moving average coefficient of 0.4. What is the value of the autocorrelation function at lag 1?

What is the optimal three-step ahead forecast from the AR(2) model given in question 14?