This book gives a systematic, comprehensive, and unified account of modern nonparametric statistics of density estimation nonparametric regression, filtering signals, and time series analysis. The coverage is suitable for a one-semester course for advanced undergraduate and graduate students with majors ranging from statistics and engineering to medicine, business, and the social sciences. The prerequisites are intermediate calculus and introductory probability. Numerous exercises of various levels of difficulty, given at the end of each chapter, will be very useful for the instructor and for self-study.