Components of Time Series (Trends, Seasonal, Cyclic and Random variations) Lecture # 09

Описание: 0:00 Components of time series
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.
0:50 Trends
Trend shows the increase or decrease in the overall demand. So, it remains a straight line with increase or decrease in time.
2:23 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.
3:50 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.
4:16 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.
4:40 Graphs for components of time series