Normal Distribution and Z Score | Math, Statistics for data science, machine learning

[@dipto624]

"How normal distribution is used in data analysis?" - All I needed was this answer. N it took me 1.5 months to get a proper answer. I got bombarded everywhere with theories no one explained how to use it.. Thanks man. I loved your teaching style. This is the problem, we r using this to solve this problem. Now let's talk about what this is.. this should be the way to teach.

[@charlesjohn4097]

true

[@dwightschrute1588]

Blown away by how easily you explained such concepts, which I scared me earlier.

[@codebasics]

I am happy this was helpful to you.

[@shobhitsadwal7972]

You left Dunder Mifflin for data science ?

[@dwightschrute1588]

@@shobhitsadwal7972 They kept calling me assistant "to" manager, so had to quit :(

[@aniketchaudhary3138]

@@dwightschrute1588 You should have joined Athlead then :)

[@Arjun-dj2lc]

I just because I never seen a explanation like this

[@RJ-dz6ie]

Every student deserves a teacher like you and we are all fortunate to learn from you...the way you explain concepts with practical applications is just awesome 👏 Thank you 🙏

[@codebasics]

It's my pleasure, I am happy this was helpful to you.

[@deepakj182]

@@codebasics Looking forward to see ur videos 😁

[@sanketpatil3698]

Really, he is very good.

[@SidIndian082]

@@codebasics sir , data set not uploaded here

[@vincentdey4313]

Your dedication and impact as a teacher deserve global recognition.

[@arjunkomarla2109]

The way you made understood z-score concept by showing the graphic at first and then explaining formula made concept too easy. 👏

[@IBRAHIMDEMIREZ]

Dear Dhaval, I wish you will be finding the person same like you for all your problems. Such a brilliant explanation, simply the best so far, love you man!!!

[@learnerlearner4090]

Learnt for the first time how normal distribution can be used for outlier removal. Thanks so much for explaining the concept and why and how it's used. I like your simple python code to explain the usage of the concept. Great teaching skills!

[@codebasics]

Glad it was helpful!

[@samarun1188]

A Great Explanation of this concept , eventhough there are thousands of videos in youtube , this is very unique and clear video for explaining statistics and Standard deviation on data Science... Thanks A Lot !!!!

[@saurabhclh]

Was stuck with something similar for past 10 days , u solved it Hats off guruji

[@learn9475]

Thank you ! not even professors could take time in explaining concepts in practical way thanks for your time !

[@PrashantKumar-mj8nb]

You really make complex topics so simple and easy to understand. You are a great mentor 🙏

[@codebasics]

👍🙏🙏

[@deepthireddy3267]

I have watched many videos to understand Z-score in real time data, no one explained this way. I never forget the concept in lifetime. Subscribed the channel and never miss your updates. Hats off to you!

[@codebasics]

Thanks for the feedback Deepthi 👍

[@supersql8406]

What a great teacher... not only easy to follow by his guidance but he shows you other ways of doing things along the way which is great for learning!

[@codebasics]

glad you liked it :)

[@Ropit12841]

Couldn't figure out the use of normal distribution in data analysis.. finally got my answer.. thank you so much

[@rakshayani-c3q]

Great content!! thank you!! If the playlist is in below format it will be more useful. Descriptive Statistics: Mean, Median, Mode: Understanding central tendency. Range, Variance, Standard Deviation: Measuring data dispersion. Percentiles, Quartiles: Analyzing data distribution. Inferential Statistics: Hypothesis Testing: Formulating and testing hypotheses about population parameters based on sample data. Confidence Intervals: Estimating the range within which a population parameter is likely to fall. Significance Levels: Understanding and setting significance levels for hypothesis tests. Probability Distributions: Normal Distribution: Understanding and working with the normal distribution. Binomial Distribution: Relevant for analyzing binary outcomes. Poisson Distribution: Used for counting events over a fixed interval. Correlation and Causation: Correlation Coefficient: Measuring the strength and direction of a linear relationship between two variables. Causation Awareness: Understanding that correlation does not imply causation. Statistical Tests: T-Tests: Comparing means of two groups. Chi-Square Test: Analyzing associations between categorical variables. ANOVA (Analysis of Variance): Comparing means of more than two groups.

[@laddukavali3324]

Thanks for the excellent explanation ❤❤🎉

[@vaibhavsrivastava5787]

This video made my day, you made this so simple now I understand the concept of STD Deviation & Normal Distribution. Thankyou Dhaval Sir:):)

[@codebasics]

Thanks Vaibhav.

[@pedrinchipedrinchi07]

- Gracias por estos vídeos, son píldoras de información valiosa para los que hemos comenzado en este mundo, ya sea por la estadística o el código aplicado. - Thanks for these videos, they are pills of valuable information for those of us who have started in this world, either because of the statistics or the applied code.

[@debarunkumer2019]

Love how articulated are the contents. Waiting eagerly for the upcoming videos on this topic.

[@codebasics]

Very soon!

[@debarunkumer2019]

@@codebasics thank you so much

[@universal4334]

I couldn't wait for further videos. How neatly you are explaining 🥳

[@codebasics]

More to come!

[@DeepaDeepa-yb6bw]

Excellent first I tried to unstd the nd in Google in many websites couldn't unstd but your video tells inch by inch info about nd.....thank u man

[@arunraja1082]

Thanks for explaining in a simple manner and with a real time example. Got a clear understanding about statistics concepts .

[@codebasics]

Glad it was helpful!

[@arunraja1082]

@@codebasics Yes sir

[@nikhilreddy4582]

What ah explanation man really👌👌. now i got confidence...that i can also start my career in data science

[@darshakkumarranpariya867]

Sir, you are so good at learning and teaching. Please make video about your learning methods/strategies. 🙏

[@AZIZULHAQ-j8c]

Your explanation of the topics is good.

[@bhaskarg8438]

Very clear to understood the concept and how and where to apply in Data Science , Thanks a Lot

[@codebasics]

Glad it was helpful!

[@ahmedtawfiq3625]

This is really helpful for my statistics course 🙌🏼

[@codebasics]

Glad it was helpful!

[@pravindilipvedpatak540]

This video is so usefull for me i m bad in stat but the way of teaching u did that was awesome , thank you so much

[@codebasics]

Glad it helped

[@piyushkumarsahoo547]

You have really explanied in a very unique way, loved your teaching!!

[@goodwork9577]

Really good explanation but when i tried to perform the exercise, i was blank because of the approach for getting 1st question. I kept on following how it was did in video but it was totally different. All i can is thank you providing such exercises, it really helps to learn new things from errors.

[@codebasics]

Glad it was helpful!

[@BiranchiNarayanNayak]

Excellent explanation. Simple & Easy understanding.

[@codebasics]

Glad you liked it

[@jyotimahajan997]

Explanation of the concept is so simple that any one can easily understand.waiting for the next video 👍

[@codebasics]

I am happy this was helpful to you.

[@maheshh_xv]

The way you explain is just amazing

[@codebasics]

Glad it was helpful!

[@arghasen8236]

Thank You very much sir! I am following your data analysis roadmap and your videos are really helpful to learn MAD, SD , Bell Curve , Z score such interesting topics. Now I can feel that ya Learning Statistics is really fun

[@nasrullahturke4480]

In this example we have calculated mean with outliers part of calculation. Outliers at first affect any measure of central tendency. Normal distribution is used to find the zo score and the associated area under curve as a Probablity.

[@chandranks]

Z score concept easily understood. With your examples. I am using R for analysis. To learn the statistics concept ony i watch your video.

[@codebasics]

I am happy this was helpful to you.

[@neerajCHANDRA]

Very informative video with nice explanation ❤

[@danielq1985]

Well done sir! Super helpful, A+ teaching ability!

[@codebasics]

Glad it was helpful!

[@zaedgtr6910]

All i can say is thank you so much for the hands on.

[@gavint.7304]

Amazing video for normal and z-score, thanks

[@reshuraj5252]

Please make more videos in which theory + practical both should available with more explanation....& thanks a lot for making these type of videos...Really it's very helpful for us.

[@codebasics]

I will try my best. I am happy this was helpful to you.

[@afseena4613]

Thanku so much sir, you are my mentor my datascince path

[@tobyroy336]

You are one fantastic teacher

[@RajeshKumar-ht4di]

Very nice explanation with practice and theory.. Really great one

[@codebasics]

Glad it was helpful!

[@vishalbhapkar2359]

hello, @codebasics.. this is amazing stats series as you do always, pls keep this series continuous and update videos as early as possible i'm eagerly waiting for the next videos

[@funtime12345]

I am following all your videos!! Thanks for being such a nice teacher!!

[@codebasics]

Happy to hear that!

[@sharmilasherin4788]

your class is just awsome

[@Rustincohle88]

Man you are a genius 🙏

[@aliasjad9560]

Sir, you are amazing please make a tutorial on the hypothesis testing

[@observer698]

Yes please!!!! that is also very confusing for me too...

[@asamadawais]

Excellent explanation again!!

[@architpatel3032]

Thank you sir for creating so informative videos that not only are inspiring us to learn theoretical concepts but also do hands on practice by using your notebooks :) I tried using histplot but was getting error, updated my seaborn library to version 0.11.1 but still faced the same error. I was able to plot the graph by using distplot.

[@kodidalamaheshbabu9242]

Simple and Clear .. thanks a lot !!

[@codebasics]

Glad you liked it!

[@giblyfgiblyf]

sir, You are the BEST!

[@ShreyasSinha-v6g]

Best Explanation, Thank You

[@AbubakerMahmoudshangab]

Thank you very much sir for your amazing videos

[@n1984ster]

superb explanation...

[@manasaraju8552]

Thank you for sharing this content sir

[@KapasiTejasVideos]

Nice Explanations!

[@trieuluu921]

Thank you for your amazing work

[@venkat2ram]

It's a really nice explanation. You have shifted to maths after 7 videos in this playlist. That's all the stats we need for data science? OR you are covering only for beginners? I am a beginner and I want to know if I need to know more than your playlist. Thanks.

[@markmcleod6376]

Love your videos!! Very educational and well done. Thanks!

[@codebasics]

Glad it was helpful!

[@rajan4982]

The very idea of creating a stat and math series is brilliant. Coding without any understanding of the underlying concept is a bit meaningless and frankly not reliable. And you explain well.

[@AbhishekSherawat]

Thanks u sir keep make more video related to these topics , Keep it up 😎😎

[@codebasics]

Keep watching

[@savanirutvik2263]

very very helpful and easily explain . please sir make a full playlist of mathematics and statistics required in data science

[@codebasics]

Glad it was helpful!

[@ahmedtawfiq3625]

These videos are so helpful

[@codebasics]

Glad it was helpful!

[@akshayjain8841]

Saras Sir 👌

[@codebasics]

Thank you

[@ashvinraj1311]

Ur the Master (can u do vedio life of working in day (data scientist vs data analyst)

[@harishkannan8023]

Awesome explanation

[@codebasics]

Glad it was helpful!

[@marnisrinu5619]

Excellent Videos.

[@codebasics]

Glad you like them!

[@mvcutube]

Nice explanation of topic. Thank you

[@codebasics]

Glad you liked it

[@ravindra2141]

Nicely explained sir.

[@codebasics]

Glad it was helpful!

[@vaniagrawal6211]

Sir, please provide a video on function approximation. Just love your lectures.

[@AjaaySetti]

Thank you sir ❤

[@shahbazzkhalid]

amazing teacher air

[@codebasics]

Glad it was helpful!

[@binaykumar1616]

Great explanations

[@codebasics]

Glad it was helpful!

[@sayakpatra6897]

Thank you so much for this. Sir, could you please upload some more videos on Statistics? Please

[@himanshusemwal1889]

Sir nice video.very helpful

[@vivekpaliwal1876]

Good explanation

[@nigamaveena4211]

Tq so much sir... Hoping more videos on metrics and math in algorithms.

[@codebasics]

Keep watching

[@nigamaveena4211]

@@codebasics sure sir.

[@ahmedtawfiq3625]

Thank you so much for your amazing contents ❤️

[@ahmedtawfiq3625]

So well explained

[@ArunKumar_237]

Slowly I feel that I can become data analyst

[@gaganparnami5720]

Very Informative.. Great explanations.. when is the next video.

[@codebasics]

Very soon, Glad it was helpful!

[@SmitNReyansh]

Very informative.. thank you

[@codebasics]

Glad it was helpful!

[@sureshdr6274]

Hi , exolaination is very nice , am having 3 yrs experience in java domain and now am learning data science , can you recommend me any projects so that i can add that to my resume.

[@fatemehshahsavari9240]

Thank you for the great explanations on std and z-score. I was wondering in the Kaggle example of people heights, why you chose (3) and (-3) to remove outliers using the z-score? Was that a rule of thumb or was it related to the value of std which was 3.84?

[@mohammedjaffarmagi]

Hero ho tum hero mere liye

[@keynotesl]

thank you very much, sir. very valuable content.

[@codebasics]

I am happy this was helpful to you.

[@rishu6103]

Amazing

[@codebasics]

Glad it was helpful!

[@naumanjn]

Amazing .Awesome.

[@codebasics]

I am happy this was helpful to you.

[@nithinanthony1724]

god will bless you sir

[@Homeybadgers]

Thank you , you are an amazing teacher. QQ: If standard deviation and Z-score are similar; why do we even use a Z score? What problem does a Z-score solve that standard deviation doesn't?

[@bhaskarkothakota2296]

Lv u 3000 brother 😎

[@bilalhassankhan221]

plz add sequence number in every video bcoz that is bit confusing which topic should I learn first... plz do this in the upcoming videos..

[@Malayalam_learner]

Thanks 🙏

[@ahmedtawfiq3625]

Waiting for more contents

[@martintrapp1992]

How do you pass z-score to ML algorithms? Do you normalize them before let them go through the neurons? Their values are pretty much close to 1 and 0 but not all of them. Also heard z-score is a good way to normalize datasets, but is it required to scale them between 1 and 0?

[@AshishPatel-kn3kc]

thanks lot for putting this videos, it is really helping. Do you have video on R2 score and P-values with use cases.

[@hashwel9649]

Hello Sir, thank you for your very good videos. I had a bit of trouble understanding where the 0.61 Standard Deviation came from when calculating Z score. So I tried to calculate it myself and i found 0.57, I'm sure I followed the steps correctly, please let me know if not the case. I did each data point minus the average (5.25) then squared it. Then i found the mean of all those by adding them up together and dividing them by 9 (because there are 9 data points). I found 0.335 for this. Then I found the square root which was 0.57 This is how you calculate standard deviation right? I am confused why I did not find 0.61 like you did.

[@learnerlearner4090]

Pls. let us know what are lower and upper bound percentiles. Kindly explain the usage of the quantile function used. Thanks.

[@learnerlearner4090]

Got to know about it from the Median, Mean, Mode, and Percentile tutorial video. Thanks so much!