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?

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

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

If there are three variables that are being tested for cointegration, what is the maximum number of linearly independent cointegrating relationships that there could be?