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  1. swaplaw007
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    Seasonality is a pattern which you will encounter in your time series data at specific intervals
    over and over again. For example, if you plot the ‘amount of crackers burst’ against all the weeks
    in a year, you will come to know that it shows spikes during the festive seasons and you will find this
    pattern every year.

    Cyclicity on the other hand, is very similar to seasonality but it has to be determined over large
    time periods. For example, recession, you will see this occurring in cyclical patterns again and again after
    a gap of several years.

  2. Ognish
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    A seasonal pattern exists when a series is influenced by seasonal factors (e.g., the quarter of the year, the month, or day of the week). Seasonality is always of a fixed and known period. Hence, seasonal time series are sometimes called periodic time series.

    A cyclic pattern exists when data exhibit rises and falls that are not of fixed period. The duration of these fluctuations is usually of at least 2 years. Think of business cycles which usually last several years, but where the length of the current cycle is unknown beforehand.

  3. Shubham Bhatt
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    Differences between seasonal and cyclic patterns:

    Seasonal Pattern is a periodic pattern which exists due to a calendar (eg: quarter, month or day of the week) whereas Cyclic is a pattern where the data exhibits rises and falls that are not of a fixed period (duration usually of atleast 2 years)
    Seasonal pattern ihas a constant length whereas cyclic pattern has a variable length
    Average length of cycle longer than length of seasonal pattern
    Magnitude of cycle more variable than magnitude of seasonal pattern
    The timing of peaks and troughs is predictable with seasonal data, but unpredictable in the long term with cyclic data.

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