Time series decomposition seeks to separate the time series (Y) into 4 components: trend (T), cycle (C), seasonal (S), and irregular (I). What is the difference between these components?

Time series are particularly useful to track variables such as revenues, costs, and profits over time. Time series models help evaluate performance and make predictions. Consider the following and respond in a minimum of words:

• Time series decomposition seeks to separate the time series (Y) into 4 components: trend (T), cycle (C), seasonal (S), and irregular (I). What is the difference between these components?
• The model can be additive or multiplicative. When we do use an additive model? When do we use a multiplicative model?
• We have different ways of showing and projecting trends in a time series. the three most common are moving averages, exponential smoothing and our new friend regression analysis. How might any of these be used? Have you seen any in use?