Time Series is a set of properly speared numerical data which is obtained through a variable known as response variable at regular intervals of time. The forecast made is based on the past values only. The basic assumption in underlying the forecast is that the factors of the past will be present in the future too. Data obtained for time series has to be in set of sequences. Data should be collected from a proper channel and it has to be evenly spaced between the time periods. Time series are dynamic it changes over the time. When we work with data which is related to times series we have to make sure that the data is plotted so it is available for a view. The main components of times series are as follows:
a) Trend: trend shows the upward and downward trend on the plotted area, this fluctuation may be due to population, age etc.
b) Cyclical: these trends occur due to interaction of factors which are strong enough to influence the economy.
c) Seasonal: these occur due to seasonal changes in fashion, customs, wheatear etc.
d) Irregular Components: occur due to changes in the events which are not known to the company like strikes, wars, etc.
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