in the PACF plot for the partial auto co-relation fn, if the 6th or 7th value on the x axis is outside the green line do we still consider the 7th value in modelling the Partial auto co relation fn ?
Hi Nachiketa, at the last of this video, there was a PACF plot and i think we should take 3 lags there instead of two, as the 3 rd lag is also not within the line.
could anyone specialist help me I want to ask before I go to the next step, my problem it's with my data I have, I have land prices for 560 plots for the last 11 years, should I consider all the plots prices or the average mean would be enough, the second question do you think should it be the prices for each year quarterly prices, or annual prices is enough?
I had to reupload this video, since the previous upload got a copyright claim because of the intro music used.
tHIS GUY EXPLAINS concepts in such a simple language which is easy to understand. Why do people unnecessarily make these things complicated?
Your simple Realtime Examples are awesome 👌 . You have 2 Profession in hand
A Teacher and a Data scientist. Continue the Same👍
Best explanation on how to infer from a PACF plot. Amazing.
Wow! This channel is criminally underrated. Thank you so much for your amazing videos Nachiketa!!
You're a gem, brother!
Thanks!
such a great video man, crystal clear explanation.......thanks a lot!!!
Thank you so much! Very easy to understand
You're welcome!
in the PACF plot for the partial auto co-relation fn, if the 6th or 7th value on the x axis is outside the green line do we still consider the 7th value in modelling the Partial auto co relation fn ?
Hi Nachiketa,
at the last of this video, there was a PACF plot and i think we should take 3 lags there instead of two, as the 3 rd lag is also not within the line.
Great explanation brother
You calculated the error at last.Then what we have to do with it?Am new but I can understand yours well thanks and please clear my doubt.
Bro you are awesome. keep it up.
Good one sir
Hi, so if two variables are related or auto-correlated then what do we do ? Do we take steps for prediction or do we do some more data processing ?
C is coefficient right
could anyone specialist help me I want to ask before I go to the next step, my problem it's with my data I have, I have land prices for 560 plots for the last 11 years, should I consider all the plots prices or the average mean would be enough, the second question do you think should it be the prices for each year quarterly prices, or annual prices is enough?
Is it equal to linear regression sir?
Thanks :)
👍
diletant