Time series decomposition seeks to separate time series $($Y$)$ into trend components $($T$),$ which represents long term progress and the overall direction $[$increasing$/$decreasing$/$staying constant$],$ seasonal components $($S$),$ or the repetitive short term cycle $[$approximately a year$],$ cyclical components $($C$),$ reflects the fluctuations near the trend line, and irregular components $($I$),$ which shows random variations that are unattributed to other components, and are completely unpredictable.