This book offers a simplified approach to random processes for the non-specialist and advises the reader on how to best predict its behavior, both from raw data and theoretical models. With a premise based on the idea that new techniques are best introduced by specific, low-dimensional examples, rather than attempting to strive for generality at the outset, the mathematics is easier to comprehend and more enjoyable. It distinguishes between the science of extracting statistical information from raw data - e.g., a time series about which nothing is known a priori - and that of analyzing...