The effect of long-term causes is seen in the trend values we compute. A trend is also known as ‘secular trend’ or ‘long-term trend’ as well. There are several methods of isolating the trend of which we shall discuss only two methods which are most frequently use in the business and economic time series data analysis. They are: Moving Average Method, and Method of Least Square.

While considering matters such as trend of prices, sales, profits, etc., a particular type of average known as moving average is used. It is a measure of trend (long-term tendency of the data) in the time series data. Moving average is an arithmetic average of data arising over a period of time and is calculated by replacing the first item in the average by the newly arising item.

Each moving average is based on values covering a fixed time span which is called “Period of moving averages”.

The successive averaging process does a smoothing operation in the time series data, i.e., it irons out fluctuations of uniform period and intensity. They can be completely eliminated by choosing the period of moving average that coincides with the period of the cycles i.e. periodic movements. Even if the periodic move with the period of the cycle i.e., periodic movements. Even if the periodic move merit is absent in the time series, the irregularities of data can be reduced to a large extent by moving average process. If we choose this method, we should select a period for calculation. The period may be 3 years or 5 years or 6 years or 12 years etc., which is to be decided by considering the duration of the cycle.