Stationarity & Seasonality| Time Series Forecasting #1|

Time series anlaysis and forecasting are huge right now. With the enormous business applications that can be created using time series forecasting, it becomes crucial to dive into depth of this subject.

In this video i talk about the following things which are absolutely essential before learning time series models:
1)Stationarity ,
2)Why is stationarity required and how to convert non stationary time series into stationary
3)Seasonality and how to remove seasonality from a time series
4) We will also look at various time series plots to master the skills of identifying if a times series is stationary or not

Recommended Books to get better at Time Series Analysis and Python:

Leave any queries in the comments section and thanks for watching !

[jinks]

Dhanyavaad. As a data scientist I found this was very helpful

[pyjryrv]

amazing content> very superb man i understood each and everything. For this shit i am paying 4 lakh rupees in a university in United states but cannot understand anything here. But this guy made it so simple. Thanks man. Reallly appreciate.

[louisa]

Thanks for your videos! I'm new to time series forecasting and your content gives me a good overview. I noticed though while reading more on the topic that you might have mixed up first order differencing with lag difference. What you describe ( Y(t) - Y(t-2) ) seems to be called a lag-2 difference and apparently order is how many times you do the whole process.

[teetanrobotics]

Love the playlist on Time Series Forecasting. Hope you upload more videos.

[swapnadeepghosh]

bhai apne itna accha knowledge kaha se liya ??... thanks for passing it brother
GOD bless you

[ankitayadav]

its really good vedio to understand concepts, good work

[harinatha]

This video is worth watching....!
Can you please make a video on Augmented Dickey Fuller test.

[lakshyadaulani]

please do make a video in mathematical calculation in both statistical tests for stationarity

[joshpeters]

Okay so what is the interpretation of the final result vs the exponential curve?

[anuragpatil]

Thanks for the video !! superb explanation

[Jevuify]

Nice explanation. Your channel is underrated

[dicloniusN]

in python arima there is auto differencing? we don't need to fit model with this differenced time series? just select 'I' value? second param

[hrsh]

I understood the differencing part, but I have a question. If we take the differencing and reduce the scale of data from 400-500 to 0.1-0.5, wont we have trouble scaling the output later ? and if we take the differencing from the data to make it stationary doesnt it mean that we are changing the nature of the data and instead we can use a better model that can work with the current state of data ?

[chandu]

Well explained. Looking forward to more content.

[medhavanisharma]

Hello Nachiketa Can you just tell me if there is any videos regarding the theory content on this particular topic...

[sulagnanandi]

how can we get the actual predicted values back when converted data to stationary?

[nurulain]

Can you share example of forecasting using hybrid models?

[siddhijain]

Thankyou for such simple explanation! Great!

[abhishekagarwal]

very nice explanation
i wanted to know can i do time series analysis on yearwise median income of men in any particular country???

[pragyabhardwaj]

Please make a video for statistical test