Components of Time Series (Trends, Seasonal, Cyclic and Random variations) Lecture # 09
Mech UET Peshawar
Published at : 26 Dec 2020
This lecture explains the basics of the forecasting techniques. The understanding of these components is very important before moving directly into the prediction of the future demands.
Trend shows the increase or decrease in the overall demand. So, it remains a straight line with increase or decrease in time.
2) Seasonal Variations:
Seasonal variations are the fluctuations with the time after a repetitive regular period of time. This seasonal variation is generally taken with in a year or in other words repeated with in a year.
3) Random Variations:
Random Variations can not be predicted in the time series. because these variations are due to an unknown reason and it might be due to an unpredicted change.
4) Cyclic Variations:
This is the variations for a very ong duration. and we need a huge previous data for its prediction. And these fluctuations are very complicated.
Components of time seriestrendseasonal