Components of time series Assignment Help

Time Series - Components of time series

Statistics >> Components of time series

The changes in the values of a variable with respect to time can be the resultant effect of a variety of factors. These factors can be classified into four categories which are called the components of time series. Some or all of the components may be present in any time series with varying degrees. The components are as follows:

(a)    Secular Trend or Trend

(b)    Seasonal Variations

(c)    Cyclical Variations

(d)    Random or Irregular Variations.


The trend is the general long term movement in the time series value of the variable over a fairly long period of time. The trend of a series is generally either upward or downward in nature. For instance, the data relating to population, production, literacy etc have upward trend while the data relating to death rate, illiteracy, epidemic etc. have downward trend. However, such a trend may not always hold good. It is to be noted that depending on the nature of increase and decrecase, trend may be linear as well as non-linear. Again long period of time can not be defined exactly and it would depend on the nature of the problem.


The study of trend helps a businessman in forecasting and planning his future business activities. It helps an economist in formulating economic policies. It is used in making comparison between two or more time series. By isolating trend from the given time series we can study the short-term and irregular variations.

Seasonal Variations

Seasonal variations refer those pattern of change in a time series that repeat over a period of one year or less and they repeat from year to year. They can be studied when the data are recorded at half yearly, quarterly, monthly, weekly etc. They cannot be studied when the data are recorded annually. Seasonal variations occur regularly season after season and therefore they are definite and can be foreseen with a little effort. They are due to the following two reasons.

(i)    Natural Cause

Changes in the climate and weather conditions have a profound effect on seasonal variations. For example, the sales of umbrella pick up very fast in rainy season, the demand for cold drinks goes up during summer etc.

(ii)    Man-made Cause

The social customs, traditions and conventions play an important role in fixing seasonal variations. For example, during festivals like Bihu, Puja, Id etc. the sales of many commodities go high, the price of ornaments go high during marriage seasons etc.


An accurate assessment of seasonal variations is an aid in business planning and scheduling such as in the area of production, inventory control, personnel, advertising and so on. A knowledge of seasonal variation helps a consumer in purchasing the articles at least prices during the slack seasons.

Cyclical Variations

The cyclical variations refer to the movements which occur after time intervals of more than one year. These are the changes that take place due to economic booms or depressions. The cyclical variations, though more or less regular are not uniformly periodic. One complete period normally mean 7 to 9 years. Series relating to prices, production, wages etc. are all affected by business cycles. Business cycle is composed of four phases, namely-boom, recession, depression and recovery. Each phase change gradually into the next phase


The knowledge of cyclical variations is of great importance to businessmen in the formulation of policies for stabilizing the business activity. With a knowledge of cyclical variation a businessman can face the challenges of recession and depression by taking the appropriate' decisions in advance. 

Random or Irregular Variations

As the name suggests, these variations are random, accidental or simply due to chance factors. These variations may be due to such isolated incidents as floods, famines, 'wars, earthquakes etc. which are completely irregular in nature. Thus, they are wholly unpredictable. This includes all types of variations in a time series which are not attributed to trend, seasonal or cyclical variations, 

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