I know you made this video 9 years ago, but I just want you to know that you're still helping students till' this day. Your explanation is very clear and I have finally grasped this topic after many trials and errors. Thank you so much
I ran a least squares regression using a calculator. You go into the stat lists of your calculator and put in the coordinates (1, 71) (2, 71) (3, 71) (4, 63) (5,73) & so on for all the data points. Then depending on your calculator the next step is different. You go into the stat menu and get a Linear regression. It probably looks like LinReg(a+bx) or something like that. It'll give you an equation based on those data points. What model of calculator do you have? I could google the steps for you
Thank you for this, i want to know based on you chosen 1 then 2 then 3.... for the regression line equation is it based on the sequence of periods ? if that yes,, how we can know the actual sales when we go from quarter to monthly ? " what i mean the level of period details " for example, you calculated 77.82 for 2006 Q1 , what the the sales for Jan?Feb?Mar? in this quarter ?
There are 4 quarters. Step 1: Center the means - Q3/2003: 68.875, Q4/2003: 69.50, Q1/2004: 69.875, Q2/2004: 71.75, Q3/2004: 73.625, Q4/2004: 74, Q1/2005: 74.625, Q2/2005: 75.75 Step 2: the proportion Quarterly Sales/Centered Mean.- Q3/2003: 0.914700544, Q4/2003: 1.079136691, Q1/2004: 1.073345259, Q2/2004: 0.919860627, Q3/2004: 0.869269949, Q4/2004: 1.202702703, Q1/2005: 1.018425461, Q2/2005: 0.897689769 Step 3: Work out the unadjusted seasonal index Q1: 89.20%, Q2: 114.09%, Q3, 104.59%, Q4: 90.88% Step 4: The average of the above unadjusted seasonal index: 99.69%, which should be adjusted to 100%. → The adjusted ratio is 1/99.69%=100.312% Step 5: Seasonal index: Q1: 89.20%*100.312%=89.48%, Q2:114.45%, Q3: 104.61%, Q4: 91.16%
You count up each data point you have, sequentially. I explain it later in the video in relation to question 13 from the exam. But basically Q1 2003 is your first data point so you can that x=1. Q2 2003 is second so that's x=2. Q3 2003; x=3. Q4 2003; x=4. Q1 2004; x=5. Q2 2004; x=6. Q3 2004; x=7. Q4 2004; x=8. Q1 2005; x=9. Q2 2005; x=10. Q3 2005; x=11. Q4 2005; x=12. and then we get to... Q1 2005; x=13.
How would you calculate the seasonal indices if you had an incomplete data set for 2005. Say you have all of the data from Q1-4 for 2003 and 2004 but only Q1 and Q2 for 2005? Would you only use 2003 and 2004 to calculate the seasonal indices?
Helpful video, but I think when finding the equation of the least squares trend line for the deseasonalised data you entered the wrong formula of Y=a•x+b. I entered a+b•x and got a different answer.
Hi, I have a 12 month data . Demand for sure is seasonal. But the sum of seasonal index is not coming out to be one as at some places net demand is negative or zero. In that case, will my seasonality calculation hold right?
Hi, I need to depersonalised my daily bus ridership data but I need to remove the effect of two periods. they are month of year and day of week both. how do I depersonalised them. should I depersonalised day of week first and then take that depersonalised data to depersonalised the month of the year. please let me know. thank you
Could someone help me figure this out, thanks! *Question 12* *The seasonal index for heaters in winter is 1.25.* *To correct for seasonality, the actual heater sales in winter should be* A. reduced by 20%. B. increased by 20%. C. reduced by 25%. D. increased by 25%. E. reduced by 75%. _This has been take from VCAA Further maths exam 2014_ I know for a fact that this is how you solve it : _1/1.25= 0.8_ and the answer therefore is A; but *where did the "1" come from?*
+Monkey D. Luffy 1 is the weight given to every period being considered. So if we have four quarters, 1 is given to each, adding up to 4 for the year. Similarly, if there are 12 months being considered, 1 is assigned to each period, making the annual sum as 12. Hope this helps.
Not sure what you mean... have I made a mistake at those points? Have a spelled something wrong? Eeek! I've watched those bits and I can't figure out what you're referring to, sorry! Are you just highlighting the useful parts so people can skip past all my waffle?? Hehe. That would be useful, I'm guessing :)
I know you made this video 9 years ago, but I just want you to know that you're still helping students till' this day. Your explanation is very clear and I have finally grasped this topic after many trials and errors. Thank you so much
facts
In 2022
It's helping tutors, too :)
Oh Ok, well that's a relief. Thanks for the reply. It's good to know that lots of students are finding it helpful!
12 years kater and it still helps me a lot!! Thank you so much
Incredibly helpful and well explained; you did a much better job than our MBA prof. Pleasant voice to listen to without any distractors. Thanks again!
That's the spirit!! It might sound odd, but a positive attitude helps so much. Good luck with your exam!
This scored me a lot of marks for my exam, Thank you very much❤
Finally a proper video! Thank you so much!
You explained it so simply, thank you
Thanks so much. This was very helpful and easy to understand before the day of my test!
Ur a genius thank u so much, god bless
you are a genious hey.. God bless you so much, noone does it better than you
Thank you very much! great work! Will help my for my exam soon. Thanks
Presentation is clear and easy to follow well done
thank u so much ... it really helps me a lot .. praying for you
Thank you. I found this to be very helpful
I ran a least squares regression using a calculator. You go into the stat lists of your calculator and put in the coordinates (1, 71) (2, 71) (3, 71) (4, 63) (5,73) & so on for all the data points. Then depending on your calculator the next step is different. You go into the stat menu and get a Linear regression. It probably looks like LinReg(a+bx) or something like that. It'll give you an equation based on those data points. What model of calculator do you have? I could google the steps for you
This part, I dont really understand :(
Excellent video, really helped. Thanks
youre better than my teacher! i feel im going to ace my Exams this year
LIFE SAVER. My gratitude to you.
Wow! How i wish you were my further maths teacher! Great help :)
Great piece of work.
Teşekkürler from Turkey! Veeery helpful for university midterm!
i enjoy your method of teaching
thnx mam
@supershrimp1 You're most welcome. Good luck for the exams. Nearly at the finish line!! :-)
I cannot believe I only just discovered these!.... an hour before my exam!
Thank you for this, i want to know based on you chosen 1 then 2 then 3.... for the regression line equation is it based on the sequence of periods ? if that yes,, how we can know the actual sales when we go from quarter to monthly ? " what i mean the level of period details "
for example, you calculated 77.82 for 2006 Q1 , what the the sales for Jan?Feb?Mar? in this quarter ?
A wonderful video!
Thank you very much ,GOD bless you
How did you get y= 0.78x + 67.68???
By fitting the least-squares regression
Thank you so much for this video!
thank you very much , my gratitude and God bless you
Hi. Thank you for this. This is very informative. Can i use this method to forecast daily sales?
Great tutorial, how would you deseasonalise that data??????
Great video
Can you do a video doing seasonality based on CMA? Thank you
If i pass core tomorrow, its thanks to you !
There are 4 quarters.
Step 1: Center the means -
Q3/2003: 68.875,
Q4/2003: 69.50,
Q1/2004: 69.875,
Q2/2004: 71.75,
Q3/2004: 73.625,
Q4/2004: 74,
Q1/2005: 74.625,
Q2/2005: 75.75
Step 2: the proportion Quarterly Sales/Centered Mean.-
Q3/2003: 0.914700544,
Q4/2003: 1.079136691,
Q1/2004: 1.073345259,
Q2/2004: 0.919860627,
Q3/2004: 0.869269949,
Q4/2004: 1.202702703,
Q1/2005: 1.018425461,
Q2/2005: 0.897689769
Step 3: Work out the unadjusted seasonal index
Q1: 89.20%,
Q2: 114.09%,
Q3, 104.59%,
Q4: 90.88%
Step 4: The average of the above unadjusted seasonal index: 99.69%, which should be adjusted to 100%. → The adjusted ratio is 1/99.69%=100.312%
Step 5: Seasonal index:
Q1: 89.20%*100.312%=89.48%,
Q2:114.45%,
Q3: 104.61%,
Q4: 91.16%
You count up each data point you have, sequentially. I explain it later in the video in relation to question 13 from the exam. But basically Q1 2003 is your first data point so you can that x=1.
Q2 2003 is second so that's x=2.
Q3 2003; x=3.
Q4 2003; x=4.
Q1 2004; x=5.
Q2 2004; x=6.
Q3 2004; x=7.
Q4 2004; x=8.
Q1 2005; x=9.
Q2 2005; x=10.
Q3 2005; x=11.
Q4 2005; x=12.
and then we get to... Q1 2005; x=13.
Really helpful & meaningful vdo👍
If a company only has past data for 1 year, how should it go about forecasting for future months mitigating the seasonal effects?
Thank you so much!
G R A C I A S mil desde COLOMBIA. It works perfectly with animal production. I do something similar using percentage. Thanks in advance!!!
Thank you, am from Kenya
i am from Detroid
Omg so much easier than what I thought it would be. Lol mast minute study before my exam that's in 2 hours -_-
Thank you very much, God bless you :)
How would you calculate the seasonal indices if you had an incomplete data set for 2005. Say you have all of the data from Q1-4 for 2003 and 2004 but only Q1 and Q2 for 2005? Would you only use 2003 and 2004 to calculate the seasonal indices?
Hi! can we find the seasonal indices for data that only have 1-year of actual sales data?
I have 15 years radiosond temperature data. How can I calculate annual oscillation, semiannual oscillation and triannual oscillation?
Thank you so much for this video....!!! :)
THANKYOU U MAKE CRAMMING WORK
Helpful video, but I think when finding the equation of the least squares trend line for the deseasonalised data you entered the wrong formula of Y=a•x+b. I entered a+b•x and got a different answer.
Can you tell me how you got your y value of 0.78x and where did you get 67.68 from?
What annotation tool are you using to draw on screen?
Hi,
I have a 12 month data . Demand for sure is seasonal. But the sum of seasonal index is not coming out to be one as at some places net demand is negative or zero. In that case, will my seasonality calculation hold right?
it seems like i will finish my degree on record time i really dealived by this chapter
can soemone pls tell if we have predict for three more year which is 2006 2007 2008 how will we do that
can we use this same for cyclical monthly data
@mothertyler haha nah its thanks to your hard work and studying up. Good luck in the morning!! :-)
Hi,
I need to depersonalised my daily bus ridership data but I need to remove the effect of two periods. they are month of year and day of week both. how do I depersonalised them. should I depersonalised day of week first and then take that depersonalised data to depersonalised the month of the year. please let me know. thank you
that's so helpful
Thank u soooooooo much
Parts of the tutorial:
6:56 Deaseasonalising
9:02 Deasonalised Graph
15:52 Exam Questions
I don't know what depersonalise is, sorry! Do you mean deseasonalise? Not sure I can help you :(
Where did you get the numbers 0.78 and 67.68?
when you put the data in the (cas)calculator and ask for a least square.
yooooooooooooooo yung rupe what's good brah?
where did you get x=13 from? for Q1 2006?
Anybody knows why she isn’t making new vids?
you are the best :)
It's just so people can easily navigate to parts of the video which interest them :)
Can you please calculate the SI of 2006
Could someone help me figure this out, thanks!
*Question 12*
*The seasonal index for heaters in winter is 1.25.*
*To correct for seasonality, the actual heater sales in winter should be*
A. reduced by 20%.
B. increased by 20%.
C. reduced by 25%.
D. increased by 25%.
E. reduced by 75%.
_This has been take from VCAA Further maths exam 2014_
I know for a fact that this is how you solve it : _1/1.25= 0.8_ and the answer therefore is A; but *where did the "1" come from?*
+Monkey D. Luffy 1 is the weight given to every period being considered. So if we have four quarters, 1 is given to each, adding up to 4 for the year. Similarly, if there are 12 months being considered, 1 is assigned to each period, making the annual sum as 12. Hope this helps.
15:40 I found the sheet I'm working on
Why not test the data from forecast eror with MAD or TS ? How we know that forecast is well, Not wrong
Excelent!
your the bomb
Not sure what you mean... have I made a mistake at those points? Have a spelled something wrong? Eeek! I've watched those bits and I can't figure out what you're referring to, sorry! Are you just highlighting the useful parts so people can skip past all my waffle?? Hehe. That would be useful, I'm guessing :)
Hi. Only "deacesonalised" should have been deceasonalised but nothing to worry about. The tutorial is super helpful. Thank you!
It's spelt differently here in Australia @Alicia Moore
"The Hale Way"
Haha, you kept spelling deseasonalised wrong. Thanks for the video though :p
I don't know why you didn't just average the sales for each quarter first.
Tdaa
U r so fucking amazing
fanx a lot but your tone is like eish
waw
Thanx, but plz try not to shout when you say ACTUAL!
pretty please
Are you Australian?
Thank you so much!
Ur a genius thank u so much, god bless