Which of the following sets of characteristics would usually best describe an autoregressive process of order 3 (i.e. an AR(3))?

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

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

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

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

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?

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