Includes bibliographical references (pages 680-688).

Introduction -- The use of regression analysis -- Trends and smoothing -- Cyclical trends -- Linear stochastic models with finite numbers of parameters --Serial correlation -- Stationary stochastic processes -- The sample mean, covariances, and spectral density -- Estimation of the spectral density -- Linear trends with stationary random terms. Besides serving as a text book the author hopes this book will furnish a means by which statisticians and other persons can learn about time series analysis without resort to a formal course. Reading this book and doing selected exercises will lead to a considerable knowledge of statistical methodology useful for the analysis of time series. This book may also serve for reference. Much material which has not been assembled together before is presented here in a fairly coherent fashion. Some new theorems and methods are presented. In other cases the assumptions of previously stated propositions have been weakened and conclusions strengthened.