sir, In 3rd quarters of 2000 while calculating seasonal variance averages, you have written 91.35%, instead of 95.35%. therefore if we use 95.35% for the 3rd quarters of 2000,the average quarters will be 100.01%,103.02%,95.68%,101.55% and the total is 400.26. therefore we need to subtract 0.26 to get 400 as total. we have to subtract 0.06 for the 1st and 2nd quarters and 0.07 for 3rd and 4th quarters. so the total of each quarters are, 99.95, 102.96,95.61,101.48 respectively
Hello Sir! I understand how we get -0.17, (0.69/4= 0.17) but I do not understand -0.18 in 24:16 minute. Could you explain it, please? Thank you for considering my request.
It is just rounding. Because 0.69/4 = 0.1725, and I rounded it to 0.17, then they won’t add up to exactly 0.69. To make it happen I adjusted one of them by 0.18, so now they will all add up to 0.69.
Thk u so much mr john for your explanation. I want to know why the total avaerge must add up to 400 and 0 using the multiplicative and additive model respectively?
With the multiplicative method, the variations are all bit more or a bit less than a 100. On average they are 100 and if there are 4 of them then the total must be 400.
With the additive model that are all a bit more than zero or a bit less than zero, so the average is zero and the total should be zero.
you said in the video that to check that the centered averages are reasonably linear, we can put them on a graph and see if they are more or less liner but I want to ask could we not use correlation coefficient to check the linearity?
Hi sir! In the video you said to use regression analysis to forecast trend. But could you please tell how? What will we take as variable x and what will we take as variable y?
L.Thenuka says
Dear John,
If the Question asks for the Average Seasonal Variances for the Quarters,
Should the answers be +0.06,+3.13,-3.94,+1.44 OR -0.1125,+2.9575,-4.1125,+1.2675?
Thanks!
John Moffat says
The first (+0.06 etc) as explained in the lecture, if using the additive model.
Judy0130 says
sir, In 3rd quarters of 2000 while calculating seasonal variance averages, you have written 91.35%, instead of 95.35%. therefore if we use 95.35% for the 3rd quarters of 2000,the average quarters will be 100.01%,103.02%,95.68%,101.55% and the total is 400.26. therefore we need to subtract 0.26 to get 400 as total. we have to subtract 0.06 for the 1st and 2nd quarters and 0.07 for 3rd and 4th quarters. so the total of each quarters are, 99.95, 102.96,95.61,101.48 respectively
Akhrorov says
Hello Sir!
I understand how we get -0.17, (0.69/4= 0.17) but I do not understand -0.18 in 24:16 minute.
Could you explain it, please?
Thank you for considering my request.
John Moffat says
It is just rounding. Because 0.69/4 = 0.1725, and I rounded it to 0.17, then they won’t add up to exactly 0.69. To make it happen I adjusted one of them by 0.18, so now they will all add up to 0.69.
Pameh says
Thk u so much mr john for your explanation.
I want to know why the total avaerge must add up to 400 and 0 using the multiplicative and additive model respectively?
John Moffat says
With the multiplicative method, the variations are all bit more or a bit less than a 100. On average they are 100 and if there are 4 of them then the total must be 400.
With the additive model that are all a bit more than zero or a bit less than zero, so the average is zero and the total should be zero.
Pameh says
Thank you so much for your clear response
John Moffat says
You are welcome 馃檪
mannannagpal says
you said in the video that to check that the centered averages are reasonably linear, we can put them on a graph and see if they are more or less liner but I want to ask could we not use correlation coefficient to check the linearity?
John Moffat says
Yes – by all means.
mannannagpal says
Hi sir! In the video you said to use regression analysis to forecast trend. But could you please tell how? What will we take as variable x and what will we take as variable y?