- This topic has 11 replies, 4 voices, and was last updated 5 years ago by
.
- Posts
Good day, Sir Moffat.
I have a question regarding the revision mock exam, there is a question I’m confused with. Here it is:
In the time series analysis, the additive model is used to forcast sales and the following seasonal variations apply:
Quarter 1 2 3 4
Seasonal variation +5.8 -8.4 +10.2 ?What must be the seasonal variation for quarter 4?
The answer is: -7.6
Explanation: When the additive model is used, the total of the seasonal variations is zero.My question is how did they get the -7.6? I’m not quite sure what the solution is 🙁 Thank you in advance! God bless.
+5.8-8.4+10.2 = +7.6
So for them to add up to zero, the missing seasonal variation must be -7.6
A company’s annual profits have a trend line given by Y = 20t – 10, where Y is the trend in $’000 and t is the year with t = 0 in 20X0.
What are the forecast profits for the year 20X9 using an additive model if the cyclical component for that year is -30?
$160,000
$140,000
$119,000
$60,000
Marks: 2The correct answer
$140,000
In 20X9, t = 9
in the question no mention of t = 9
How did they work it out to get figure 9 for t?
The questions says that t is the year, and that 20X0 is t= 0
so 20X1 must be t = 1; 20X2 must be t = 2, and so on.
So 20X9 must be t = 9Thank you (: ) I did not read the question correctly! Yes, 9 from 20X0 to 20X9!
Very happy though I am not a dummy !
In data with a 4 year cycle,the cyclical components using the additive model are given to be :
Year 1 – 10
Year 2 – 15
Year 3 – 25
Year 4 – 220If 2015 is year 1 of the cycle and if the trend for 2019 is predicted to be 70, what is the predicted actual value for 2019?
The answer given is 80. How did that answer arrive?
2015 is year 1, 2016 is year 2, 2017 is year 3 and 2018 is year 4.
Since there is a four year cycle, the cycle then starts again.
So 2019 is year 1, 2020 is year 2, and so on.Since 2019 is year 1 of the cycle, the predicted actual value is 70 plus the year 1 variation of 10.
70 + 10 = 80
- The topic ‘Seasonal Variations’ is closed to new replies.