Rolling statistics and stationarity in Time series | How to Check stationarity of a time series

Rolling statistics and stationarity in Time series | How to Check stationarity of a time series
#RollingStatistics #StationarityInTimeSeries #UnfoldDataScience
Hi,
My name is Aman and I am a data scientist.
About this video:
In this video I explain the concept of stationarity in time series. I also explain the concept of rolling statistics like moving average. I explain with example how moving average is computed and how it smoothness the time series chart. I explain the importance of stationarity in time series. Below topics are explained in this video:
1. What is stationarity in time series?
2. Rolling statistics in time series
3.How to check stationarity in time series
4.Moving average in time series
5.Smoothing time series
6.statitical test adfuller for stationarity test in time series
About Unfold Data science: This channel is to help people understand basics of data science through simple examples in easy way. Anybody without having prior knowledge of computer programming or statistics or machine learning and artificial intelligence can get an understanding of data science at high level through this channel. The videos uploaded will not be very technical in nature and hence it can be easily grasped by viewers from different background as well.
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[@MateiCatana21]

Thank you very much your videos saved me from failing the exam! I really appreciate the way you teach, you make it easy to understand. Thank you!

[@dipendrapratap6495]

Superb explanation sir🎉🎉

[@AshrafulAlam-]

Outstanding lecture! Love it. Thanks very much

[@RamanKumar-ss2ro]

Good one again.

[@UnfoldDataScience]

Thanks a lot :)

[@MrRynRules]

Thank you Sir, well Explained.

[@pandharpurkar_]

Great job Aman..!

[@UnfoldDataScience]

Thanks a lot Shrikant.

[@komalilyaslamok]

great work

[@UnfoldDataScience]

Thanks Komal.

[@ashishbhatnagar9590]

Nice video Sir. Very helpful.

[@UnfoldDataScience]

Thanks Ashish :)

[@sandipansarkar9211]

finished watching

[@sadhnarai8757]

Very good Aman

[@UnfoldDataScience]

Thank you :)

[@ninavanleeuwen1183]

thank you!

[@nikunjgattani999]

One video on understanding what is Unit Root

[@AhmedAbdElgawad-petroAnalyst]

very good explanation .. thanks

[@UnfoldDataScience]

You are welcome

[@akshatapalsule2940]

Sir you are best !!

[@UnfoldDataScience]

Thank you Akshata.

[@mohammadummair1378]

You really deserve a lot more !!! Loved it

[@UnfoldDataScience]

Thank you so much Mohammad.

[@amitsk7780]

Absolutely..within just 8 mins I understood the crux

[@robertbencze8205]

For stationarity, did you assume that the time series comes from a kind of special random variable (wide sense stationarity I assume is the term) that has the random mean equal to its mean in time?

[@kunal1906]

530+420 = 950/2 = 475 thank you for this method

[@user-tj6ki6xw3h]

even if time series is not stationary we can still apply ml methods like lstms right ?

[@krishnabhadke6161]

nicely and properly explained sir

[@UnfoldDataScience]

Thanks and welcome

[@rutvikjaiswal4986]

You are great sir I saw your many videos. encluding Time series and machine learning

[@UnfoldDataScience]

Thanks Rutvik.

[@navketan1965]

Sir, If I am doing double exponential smoothing 5 period moving average with a software program-after 5 period exponential moving average is calculated say (X) does computer do second calculation with data X and (X-t1) (X-t2) (X-t3) (X-t4) - - - forgive me,I went to college 50 years ago..(X-t1) is exponential moving average one period prior & so on.Thank you.

[@lovleenkaur1042]

Why do we need the TS to be stationary for ML training?

[@dr.unmeshedwankar2005]

Thank you for all the amazing videos!

[@UnfoldDataScience]

Glad you like them!

[@gothams1195]

Bro, please buy big board. Your teaching is very good.

[@UnfoldDataScience]

Thanks Gotham. Sure will try.

[@i_amanrajput]

Excellent brother ! You nailed it . I have become your huge fan

[@UnfoldDataScience]

Thanks a lot Aman 😇, please share with others as well who could be benefitted from such content

[@rutvikjaiswal4986]

make a video on What is the ADFuller test? How to understand it properly? How to analyze it! please make a video on it! thank you in advance!

[@UnfoldDataScience]

Noted Rutvik

[@osuagwumartins9804]

@@UnfoldDataSciencepls what value is now T6

[@purvanyatyagi2494]

sir , i want to train an audio denoising algorithm should I go with CNN or there is a better algo.

[@purvanyatyagi2494]

i have also seen a algo using Gaussian mixture to predict noise in audio

[@UnfoldDataScience]

Gaussian mixtures should perform good.

[@madhur4255]

Thank you, Excellent presentation

[@UnfoldDataScience]

Welcome Madhu.

[@osuagwumartins9804]

What value is now T6

[@amadoum.jallow620]

How do you determine the window? Is it that you can input any figure?

[@UnfoldDataScience]

Depends on what server our purpose, like for what we want to it. Will discuss details in upcoming video.

[@AyubAli-up4bc]

@@UnfoldDataScience okay thnx sir....

[@testingyoutube915]

Can you provide notes as well

[@siddharthaborpuzari9000]

Thanks a lot..excellent playlist

[@pusarlaaishwarya5035]

What is compositional data?

[@CrisaliDan]

I cannot find your course. Could u give me a Website or link ? Thank you

[@UnfoldDataScience]

www.unfolddatascience.com please mail me at [e-mail] for any other questions.

[@AyubAli-up4bc]

SLM sir, how to plot the accuracy of different model

[@UnfoldDataScience]

Hi Ayub. We can put accuracy numbers and model name in different list/array and plot.

[@cdhanunjay5497]

1) I have a data of daily sales for 10months when i apply the seasonal difference how can i take the shift ? 2) after doing the seasonal difference or any other method to make stationary is it necessary to bring back to the normal units

[@smartzen110]

Still this smoothing method needs to be validated with other techniques

[@philemonkrop7399]

So what's the answer

[@sandipansarkar9211]

finished coding

[@ayantikabhowmik1261]

Sir why do we need to make the time series stationary before applying any machine learning algorithm?

[@VinodRS01]

+1

[@UnfoldDataScience]

Answered :)