This lecture covers p-variate spectral representations, ACVS estimation, and spectral estimation in time series analysis. It delves into the properties of spectral density functions, cross-spectral densities, and the estimation of auto-covariance sequences. The instructor explains the use of spectral estimators, the periodogram, and the impact of tapers on reducing bias in spectral estimation.