Comments

    • Avatar of John Moffat says

      It is because the seasonal variations are all above or below the averages. Some are higher than everage and some are lower that average, and because of the they should add up to zero.

      Does that make sense? :-)

      • Avatar of Javeria says

        Yes thank you so much…. one little thing we have alot of questions in our revision kit on multiplicative model and i cant find a video explaining that, i just want to know is it important and can we expect a lot of questions based on that in exams …… thanks you =)

      • Avatar of John Moffat says

        The multiplicative model is covered in this video (after the additive model).
        I would not expect there to be lots of questions on time series, but there are certainly likely to be some questions – one either or both of the two models.

    • Avatar of Rana Nabeel says

      Slam… These should add up to zero as the trend is between high and low averages, and we have four quarters in a year among them two are higher than average and two are lower than average … so if we see the scenario in an “ideal way” then we come to conclusion that with the value the trend gets higher in “first quarter” it should get lower with same value in the 2nd quarter .. and respectively same in 3rd and 4th quarter so adding up these should result in a perfect zero(Ideal Case)..

      Hope the answer of the question is satisfactory.. :)

  1. avatar says

    Hello John, just for myself to not be confuse is there mistake done in sample 2 calculation multiplicative method? quarter 4: actual / trend should be 98% and in your case its 102% I presume you divide trend/ actual? I am wrong?

    • Avatar of John Moffat says

      I think you mean slightly different from what you wrote :-)

      What you do to make a forecast is first of all forecast the trend (and this would be the same whether you were using multiplicative or additive), and then you would adjust the trend forecast by the seasonal variation to get the ‘actual’ forecast.

      There are several ways you could forecast the trend, but for exams you would effectively use the high low method. In example 1, the trend values increase from 86.00 to 107.25 (which is an increase of 21.25) over 7 quarters (although their are 8 values, there are 7 increases). So on average it is increasing by 21.25 / 7 = 3.036 per quarter.

      If we want a forecast for qtr 1 of 2003, then this is 3 quarters away from the last trend value we have (quarter 2 of 2002) and so we take 107.25 + (3 x 3.036) = 116.36.
      This is a trend forecast, but we need now to adjust by the seasonal variation.

      Using the additive model, in qtr 1 the actual is on average 0.06 more than the trend, so the forecast would be 116.36 + 0.06 = 116.96

      Using the multiplicative model, qtr 1 is 100% of the trend, and so the forecast would be 100% x 116.36 = 116.36

    • Avatar of John Moffat says

      Some are higher than average and some are lower than average – however the total difference should be zero.

      Suppose you had two numbers – 70 and 80. The average of the two is 75.

      The difference between the first number and the average is -5
      The difference between the second number and the average is +5

      The total of the differences = -5 +5 = 0

  2. avatar says

    Thanku Open Tuition was breaking my head trying to understand Seasonal Variations,after watching this I understood in 5 mins..U r grt help for people doing self study..Thanku again.

Leave a Reply