Tutorial 22-Univariate, Bivariate and Multivariate Analysis- Part1 (EDA)-Data Science

Your explanation is easy to catch. Worth listening. Accent is good. Giving the basic things along with really helps. Pliz keep doing this thing.. thank you

soo confusing

Krish Naik, I want to understand multivariate analysis better, and I found your tutorial 22 was excellent, you are a great presenter, perfect English, amazingly clear method of exploring the analysis problem with histograms, etc. But then I found tutorial 23 was recorded badly, so I could not understand your voice easily. I clicked on subscription, and heard you talking at length about your services (again, recording not clear), but most of it was not relevant to my specific need. Why can't you just show a price list of specific items? This could include little items like "how to do multivariate analysis" , or "how to do bivariate analysis", or "How to join our 6-month course to be a data scientists" , each with a price. But I am not prepared to join, just because you are an excellent teacher. I am a customer, and I want what is useful to me right now, not your views on a long-term relationship that may, or may not, be useful. But thank you for tutorial 22, and good luck.

thanks for give us for video brother. keep it up.

Sir Hindi me padhadete 😅

Very nice explanation sir✨✌🏻💯❤

thanks

Nicely explained keep it up

I have progressed so much in short time following your tutorials. I hope one day to get a job of a data scientist.

thank you sir

Thank you sir

Hi Krish, thanks a lot for your help, I have been learning a lot from you. Just wanted to know if you have a video that explains high-level end to end DS projects. I saw one that you had for Feature Engineering and wanted to know if you have one for the whole process?

dude. you are good at teaching

thank you .but please join me as member

You are a great Teacher

Quick question here, where do we use univariate analysis then?

When we use these method before cleaning the date or after cleaning

Very much easily understandable sir

Krish, you are great. I was searching for videos related to these 3 analysis but couldn't find a good explanation like this. Thank you!

thank you

Can take univariate for single input features and multivariate for multilabel classification in NLP?

Hi, hope you're doing well.
Sorry I have a question.
Is there any multivariate dataset in the internet that the variables are labeled?!!!!!
As far as I've checked the multivariate dataset that I've seen, are labeled based on observations( for example observation 1 suffer from cancer, 2 do not and....)
Now I want the variables have lables.
Is there any data set?
I'll be bery thankfull if you help me.
Thanks in advance🌸

you are a good speaker. Things to be corrected in video -> sigmoid function is non linear! hence logistic regression is non linear. Svm as you mentioned is not a non linear classifier and it is a linear classifier.

Amazing, Thank you for making it very clear.

sir can you send the this videos playist link plz sir

Thank u sir for the valuable class

plots used for multivariate analysis like PCA, PCoA and NMDS, CCA any video on that?

Which one is the best addon for getting more opportunities as a fresher in IT industry as a datascientist with higher salary option?

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awesome explanation as always! thank you so much Krish!

sir app best teacher ho bohot acha samaj aata hai appse plz keep sharing your knowledge with us and we will support you and learn new concepts of data science

it was great tutorial

in class what ever they explianed for 3 hrs, you could tell that in 15 minutes .. Content is too good ...

This is the first ever time i am commenting on some video bcz i couln't resist .

Ur teaching is little bit hard...m unable to understand in a proper way...I always want to see ur videos but when it starts.. after some time ..m exhausted

you are great bro .. thanks . very useful.. w8 for more video with lots of examples : ) thnk

Thank you for making these informative videos. Being a student of data science your videos are gem and you are the asset to students learning the subject! Please keep uploading! Thanks

Where is the playlist sir

you explain so well. thanks,

Great video. I have a problem related to the topic which I want some help with. Can anyone answer which one is correct and little explanation on how to solve it? Here is the problem:

There is an email marketing template and we want to replace it with a better template. A is the control template. We also test email templates B, C, D, and E. We send 100,000 emails of each template to different random users. We want to figure out what email gets the highest click-through rate. Template A gets 10% click-through rate(CTR). B gets 7% CTR. C gets 8.5% CTR. D gets 12% and E gets 14% CTR. We want to run our multivariate test till we get 95% confidence in a conclusion.
Which of the following is true:
a) E is better than A with over 95% confidence. B is worse than A with over 95% confidence. You need to run the test for longer to tell where C and D compare to A with 95% confidence
b) Both D and E are better than A with 95% confidence. Both B and C are worse than A with over 95% confidence
c) We have too little data to conclude that A is better or worse than any other template with 95% confidence

I need an explanation of uni-variate data analysis

Is it helpful to MBA RESEARCH METHODOLOGY AND STATISTIC ANALYSIS??

when "you should not see a 4 d diagram":-()

Thanks Krish

so useful and clear, saved me a lot of confused wikipedia surfing :)

Following your plan of full data science and reached here till now. Lot more to go and will complete also for sure. Enjoying a lot. Thanks a lot Sir!

How do I do these analyses with categorial variables?

cfvjhkh

Hello @KrishNaik sir, Many thanks for creating such a wonderful content. The links on correlation i.e. playlist for statistics, covariance and Pearson correlation are missing in the description.