This lecture covers statistical signal and data processing tools for wireless communications, including spectral estimation, signal detection, classification, and adaptive filtering. It explores models for spread spectrum wireless transmissions and neurobiological signals, as well as parametric and non-parametric signal models. Linear prediction, maximum likelihood estimation, and Bayesian methods are discussed, along with the Periodogram, Welch Periodogram, and MUSIC method for frequency domain signal analysis.