Many data include time or have longitudinal dimensionalilty. When these data include an index of time, i.e. measures at regular or periodically successive intervals, statistics that use time sequencing in some capacity are appropriate. Consequently, investing time into a comprehensive text on these topics is not lost time. The second edition of Applied Time Series Analysis With R is reviewed. The benefits of digesting this text relative to other contributions is evaluated, the extent of expertise is summarized, and the structure including key topics of the book are described.