Practical Statistics for Data Scientists - Chapter 2 - Data and Sampling Distributions

Patreon: / shashankkalanithi
This is an overview of Chapter 2 of Practical Statistics for Data Scientists. I'll be going over the first couple of chapters of this book because the later chapters cover similar materials from my Hands on Machine Learning book overview videos.
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Twitter: / kalamari95
LinkedIn: / shashankkalanithi

[@syusyu28]

ohhh Chapter2!!! I have been waiting fro that!

[@ShahzadHassanBangash]

Please make more of these loving these series

[@harshasamudrala2115]

thank you for the well presented video brother !!!!

[@Kinnoshachi]

Bro sir, for the first time in my life I feel like I’m in a book club, thank you, I can’t wait for chapter 5

[@517127]

Your videos are really useful

[@yasmeenkarachiwala9612]

Hello Shashank, Thank you so much! Eagerly waiting for the remaining chapters.

[@viktoriiauntilova7695]

Thanks Shashank ! we do like your videos ! 😍We can learn together like that ! It is very helpfull ! Waiting for more videos for this book

[@josecarrasco9840]

thank you for this video!

[@ba-en1io]

love the series!

[@RN-er7mz]

A big thanks for the series, also please make series on "naked statistics"

[@richardlinsley-hood7149]

So what would you consider the best way to analyze a U shaped distribution? Such as hourly or yearly temperatures. These form a quasi-sinusoidal pattern which gives a strongly U-shaped distribution to the data. A lot of stuff is about normal distributions but U shaped is covered much less often.

[@moroccangamereviews8824]

please do more videos like this :)

[@ludgerderyce7312]

Great work & the Patreon page is top notch

[@ShashankData]

Thank you so much! There’s much more content where that came from

[@lokeshkumar1365]

Could you please use of applied statistics in model building and AB testing for modal validation?Thanks

[@konstantinosfasoulakos5038]

Nice video, generally in Europe we use cm for measuring heights, but it is well known that the USA use foot (btw I am from Greece).

[@bhavinmoriya9216]

You use notion for writing notes? Thanks for wonderful video.

[@rameshkannan1075]

Hi Sir I need guidance on Predicting Default on mortgage loan project using R. What are the perquisites I need to enhance my skills..

[@AbdElrahman_Mohamed_faheem]

Can you share a link of notion work space of the chapter ?

[@sandipansarkar9211]

finished watching

[@dimpushah3712]

How Central limit theorem works for unsymmetrical data?

[@hescajeda]

Plis make the video with option traductor for everypeople.

[@d3v487]

Thanks for Amazing Guide. Please upload the next chapter guide 🙏.

[@ShashankData]

Thank you! It’s already uploaded

[@d3v487]

@@ShashankData sorry but I can't see the chapter 3.

[@ShashankData]

@@d3v487 Sorry I thought this comment was on the Chapter 1 video. Chapter 3 will be coming out soon

[@wilsvenleong96]

would be better to abstract the cleaning function for the height column out into its own function.

[@kli9005]

Hello, What times are your live streams? I am in the CST zone.

[@ShashankData]

I’m CST too :). 10 AM CST on thursdays and 7 PM CST on Friday’s

[@content_king3012]

I have done it exactly the same in the video but this error keeps showing up. Can anyone help me? I have followed every details in the video. TIA. # Central Limit Theorem import pandas as pd import matplotlib.pyplot as plt sample_amounts = range(10, 100, 20) for x in sample_amounts: samples = [] for i in range(1000): samples.append(player_data_import["height_inches"].sample(x).mean()) plt.hist(samples) plt.legend([str(z) + " Samples" for z in sample_amounts]) plt.title("Central Limit Theorem") TypeError: Traceback (most recent call last) Cell In [14], line 11 9 samples = [] 10 for i in range(1000): ---> 11 samples.append(player_data_import["height_inches"].sample(x).mean()) 12 plt.hist(samples) 13 plt.legend([str(z) + " Samples" for z in sample_amounts]) TypeError: unsupported operand type(s) for +: 'int' and 'str'

[@OceanAlves23]

Olá, quando teremos novos capítulos? Abraços, do Brazil/Nordeste/PI/Teresina.

[@VishalSoni-te7hy]

How can i access notes sir?

[@willosullivan1986]

Not common knowledge for me in Australia that 12 inches = 1 foot, but I'm not representative of the population!. Thanks for your contribution to data science, I love your video walkthroughs of text books.

[@ShashankData]

Haha I do have to tell myself that only we use those measurements every once and a while

[@willosullivan1986]

@@ShashankData haha you guys are off doing you're own thing! So I'm considering joining Patreon to support you (first person ever) because I find your content really valuable.. in the Discord do we have an opportunity to talk to you directly and what perks come with joining?

[@ShashankData]

@@willosullivan1986 Thanks so much for the consideration Will, yes you can talk to me directly using Discord or Patreon, and you get access to a bunch of notes I have on machine learning, Statistics and future topics

[@willosullivan1986]

@@ShashankData joined :)

[@xXHelsingGamingXx]

🤩

[@siddheshdhanawade3709]

how can i acces this notes

[@Younessss_]

bro im from italy nobody even knows what a foot is ahahaha, i just tell people i'm 6'4" cause thats what my height in cm translates to.

[@ShashankData]

Hahahaha yeah I need to be a bit more cognizant about the global audience we have in this channel. I wish we used metric here

[@tigerzero9939]

Are you trying to learn the material by teaching others while monetizing at the same time? I would not advise learning probability theory, statistics, or programming by watching these videos.

[@axeltessai1359]

33:38 sklearn.utils.resample() returns all 2732 rows from the data if n_samples is not specified. just adding n_samples=1000 to resample() will fix this. Otherwise you are just grabbing the whole same data every iteration which is why you keep getting the same mean and the same median.