Which of the following conditions must hold for the autoregressive part of an ARMA model to be stationary?

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

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?

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 a regression equation contains an irrelevant variable, the parameter estimates will be

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

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