Live Day 1- Introduction To statistics In Data Science

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Timestamps for session
01:31 Agenda
16:15 Introduction To Statistics
19:42 Types OF Statistics
30:20 Population And Sample
34:15 Sampling Techniques
53:00 Variables And Its Types
01:05:45 Variables Measurement Scales
01:13:23 Frequency Distribution
01:17:36 Bar Graph
01:18:47 Histograms

[@krishnaik06]

Check out the playlist of Statistics in hindi kzbin.info/www/bejne/baqWiZahn8aJhdk

[@rejeevesundar3982]

You are doing such an amazing job Krish. The greatest of all charity is educating people for free

[@karna621]

Please don't drink redbull it is not good for your health Just an Advice!! And thanks for this videos

[@veerapandiyakattabomman8890]

@Krish What is the headphone model you're using??

[@gautamsudhirbaghel2571]

Where can I find above slides ?? @krishnaik or anyone

[@HUMAN-qy6yw]

You have kept Stats in Playlist then why again this session?

[@walidhossain3655]

16:39 what is statistics? 18:20 what is data? 21:00 types of statistics 30:00 Population and sample 34:24 Sampling technique(1) - Simple Random Sampling 37:50 Sampling technique(2) - Stratified Sampling 42:40 Sampling technique(3) - Systematic sampling 46:00 Sampling technique(4) - Convenient Sampling 53:00 variables 55:00 Types of variables 56:00 quantitative variables 56:45 qualitative variables 59:35 types of quantitative vars 1:06:15 Measurement of variables 1:14:10 Frequency Distribution

[@a2yfacts787]

Bhai thankyou so much yaar

[@dfordata]

thanks bro accha kaam kiya

[@chetan1831]

Thanks

[@dhanjikumar9109]

pdf kha milga bhai

[@gratefulalways]

Thank you so much

[@SarimZahid-ui5ez]

🎯 Key Takeaways for quick navigation: 00:21 📊 Descriptive statistics involve organizing and summarizing data. 16:39 📈 Inferential statistics use measured data to draw conclusions. 23:41 📊 Descriptive statistics example: Finding the average marks of a class. 27:57 📈 Inferential statistics example: Comparing the marks of a classroom to the entire college. 30:06 🌍 Population refers to the entire group, while a sample is a subset of the population. 31:17 📊 In exit polls, reporters use sample data from different regions to estimate voter preferences rather than surveying the entire population. 34:23 🎯 Simple random sampling involves randomly selecting individuals from a population without any specific criteria. 37:56 📈 Stratified sampling divides the population into non-overlapping groups (strata) based on specific characteristics for sampling. 43:04 🔢 Systematic sampling involves selecting every nth individual from a population for a survey. 45:47 🌐 Convenience sampling focuses on individuals with domain expertise or interest in a specific topic for a survey. 54:03 📏 Quantitative variables are properties that can take on numerical values, such as age, weight, and height. 56:34 📉 Discrete variables are whole numbers, like the number of bank accounts or children in a family. 01:00:13 📏 Continuous variables can have any value within a range, such as height, weight, or rainfall amounts. 01:03:34 📊 Data can be categorized into discrete and continuous variables, with examples like population being continuous and gender being categorical. 01:06:18 📏 There are four types of measurement scales for variables: nominal, ordinal, interval, and ratio. 01:07:38 🧾 Nominal data consists of categorical or qualitative variables like colors, gender, and types of flowers. 01:08:50 🏆 Ordinal data focuses on the order of values, where the value itself doesn't matter, such as ranking students by their marks. 01:11:04 🌡️ Interval data includes values where both order and value matter, but there is no natural zero point, like temperature in Fahrenheit. 01:14:11 📊 Frequency distribution tables help visualize the frequency of data categories, which is essential for creating bar charts and pie charts. 01:16:17 📈 Cumulative frequency adds up the frequencies progressively and helps determine the total count of data items. 01:19:49 📊 Bar graphs are suitable for discrete data, while histograms are used for continuous data. Histograms group data into bins for visualization. 01:24:14 📄 PDF (Probability Density Function) is a way to smooth histograms for continuous data, representing probability distribution functions. Made with HARPA AI

[@suku6904]

This series is very close to my heart :) I remember I started my data analyst journey watching this series. Finally Associate Data analyst ♥️🙂

[@swatimadankar4623]

Hey, i too am preparing to be a data analyst. Can I ask a question regarding this?

[@shivankk467]

hey can you pls share your insta id so that we can ask few questions, thanku

[@kinshukumarpurbey463]

hey, have you get placed in any company for the DATA SCIENTIST job?

[@viralthings3798]

@@swatimadankar4623 how did it go? i enrolled in data analyst course recently

[@TusharSoniTechnology]

This series is much better than Friends, Breathe, Sacred Games, Game of Thrones, etc, etc. :D

[@rottendiaries]

Thank you for giving me suggestions for TV series.

[@geek_abhishek]

Haha 😂

[@akshaypal8551]

No but important for education purpose and for entertainment game of thrones is better than it😂😂

[@moresmartsolutions9480]

ماشاء اللہ.. سر آپ نے بہت ہی عمدہ طریقے سے سمجھایا.. Love u from 🇵🇰 بہت بہت شکریہ 🤗

[@keyanwb]

You are doing an excellent job. Free education is more appreciable which needs a good heart. Thank you for your great service.

[@rokibchi]

Thank you Krish for this amzing way of teaching. Totally understandable

[@deb2372]

Enjoyed the session! Excited for day 2. Looking forward to more insightful content!

[@vagheeshmk3156]

Sir Krish Naik is more than an extra-ordinary teacher. He is an Angel in Human Form!!!

[@h-mota5348]

This interactive form of teaching and the patience you have is really very commendable!!! Thanks a ton!!!! As a self-learner in DS, this playlist is super helpful for me because its so easy to get lost in the ocean!! Much love!!

[@tavishigopal2737]

A very simple and easy explanation for interval data and ratio data is 0K, 0 F means absolute temperature. It doesn't mean that the temperature is absent. Where as the distance is ratio data, if the distance is 0 km, it means the distance is absent. The same goes for height and money.

[@satishkundanagar3237]

@33:33 - N is used to denote population size and n to denote sample size. Size of the population and size of the population represents number of elements in the population and sample respectively.

[@Shree_Ram84]

Very good explanation. Thanks it is very helpful. But one query is there.... At stratifide sampling the example you gave(41:16) for age groups (0- 10) (10-20) (10-30)....... Here 10,20,30......is repeating and hence data will be overlap. I think it should be( 0-10) , (11-20), (21-30)..... .

[@jazzitall]

I've finally found the stats course in context of data science presented in a clear way with fine examples. 🤗

[@sisports850]

Great teachers like YOU coming up with open education are a source to bring ind pak closer. Love from 🇵🇰 for 🇮🇳

[@snehalhon]

You are the besttt teacher in this whole word .....god bless you sir!!! Try to become good teacher like you

[@AagamDoshi-q3z]

Honestly your explanation for the beginner is amazing and able to relate with concepts. I have started today and I loved my 1 session and I will complete the rest.

[@whitedeviljr9351]

excellent tutorial but your convenience sampling definition is incorrect. It is the method in which a sample is taken from a population that is close to hand or at ease of access, available

[@snehashahid07]

An 18year old to be started her journey today, and as far as my research, I have found the best Teacher. Lots of love from your neighboring country Pakistan

[@asif_786]

Best video I have ever seen on the KZbin ...thank you sir for free video and your hardworking

[@chanchalarya983]

categorical variable will further divide in 3 categories, 1- Nominal Variable, 2- ordinal variable, 3-Binary variable. thank u for the informative session sir, it is very helpful

[@rajshekarsiya9114]

Everytime I watch krish videos or playlists feels good better than a movie which got nothing rather than waste of money.Thankful to be a part of watching great session

[@rishiraj6140]

Amazing session , please do bring more such sessions!

[@sabhrant7309]

This is enough for study your data science statistics video with full of concept

[@nithyapalanisamy4904]

Bar chart is for categorical variable and histogram is for continuous variables sir

[@sanichara_]

Thank you for making statistics more interesting with your examples :)

[@najiibrashiidabdi5014]

Hi krish naik my name is najiib and i am from Somaliland which is in Somalia really your explanation was good and i understand much easier so keep goin krish thank lot

[@Ironmanplayz2]

Data is simply. Pieces of information!

[@ahamadsharief384]

Thank you so much sir, you are making us to break the fear levels of Learning data science :)

[@gurjeet333]

great session, I got to learn lots of things today

[@el_professor9700]

Thank you , this class is my starting for statistics , thank you sir

[@spparida1]

Excellent teacher, very involved. Thanks Krish

[@nandagopal375]

Great work for effort statistics session 🙏🙏🙏

[@aarushim9248]

Ur literally the best person to go to for understanding anything

[@devkumaracharyaiitbombay5341]

1:04:04 why population is discrete variable

[@ridhimaridhi8602]

Ratio Variables: Ratio variables have equal intervals between points on the scale and a true zero point, where zero indicates the absence of the variable being measured. Examples: Height, weight, time (measured in seconds), age (years).

[@dzifahoyah4719]

I'm glad i opened the video. Its ACTUALLY the best!

[@hirentank5260]

Thank you so so so so so so much krish sir!!!!

[@RohitKumar-dz8dh]

Fantastic session , wish i would be there in live session . Now I am getting intrested in data science due to statistics. Thanks you lot for providing this .

[@ytustatistics]

it is really good lesson for any analitic guy. thank you very much

[@SandeepChaudhary-vx9zy]

Easy to understand..to the point only

[@onlymusic2005]

I love the way you are serious, and bring the sessions... May Allah bless you and your beloved ones...

[@riyaskhann9738]

what a an Excitement Watching Exactly 22/01/2023 uploaded 22/01/2022 thanks krish

[@dhrubajyotibarman6356]

Very good for students

[@JesalndKenil]

Very useful and informative video

[@deepanjanaroy7115]

Thankyou so much sir for sharing such a good information.

[@rajatpatil2494]

Best Teacher Ever for Data Science

[@almerandomendezjr.4742]

Great teacher, well-delivered-I love this guy's videos. Future data science enthusiast right here.

[@mayowaolowolaiyemo1606]

Great job Krish, although I missed the live session because I didn't factor in very well the time zone. You make learning really interesting 😉. Thanks again and again

[@whoashwin98]

Really appreciate this course Krish sir, thank you!

[@venkatagudala5172]

I thought 'Convenience Sampling' is when researcher collects data from a conveniently available pool of samples around or near by him/her, hence it is called 'Convenience Sampling'.

[@piyushanand8993]

great session....thankyou

[@dembasiby]

I am currently attending iNeuron Full stack DS. You guys can teach!!!! Thank you.

[@datascientistoflife8550]

shall I know Demba how was your experience and do u have any experience before enrolling..

[@dembasiby]

@@datascientistoflife8550, I have been interested in programming for the last 5 years, but I never really did it on a professional level (I am working full-time in a completely different sector). I started learning Python a few months ago, before joining iNeuron. However, I find their way of teaching great; combining detailed explanations on a very basic level and building knowledge and expertise progressively on that, with a ton of assignments and projects, in addition to the doubt clearing sessions that allow every student to get live answers to his/her questions.

[@santoshgujar5237]

Thank you, Sir, भाऊ for everything, Thank you, Sir

[@xernanpeninoy2043]

Beautifully Described, Loved the way you are teaching! Thanks for your efforts.

[@slckaz1183]

Superb sir ! compliments from Sri Lanka

[@shelmithnyambura9940]

THIS IS WHAT I NEEDED THANK YOU AND YOU ARE A GOOD TUTOR

[@lomorgaga282]

That's Great! Thank you so much.

[@tifhmad1351]

amazingly describe

[@sallymoyae3203]

Very informative, thank you

[@DinushaGalagedara]

Thank you krish keep doing new vedios, love from sri lanka

[@riasingh11]

enjoyed all the sessions thoroughly

[@navyasree7280]

Thankkyou very much for teaching everything easily.You are my saviour🙏

[@vipin2872]

Nice Explanation

[@subhanliaqat8]

thank you krish naik for this amazing content

[@shivanisharma-zn6zh]

Thanks 👍👍👍🙏👍🙏

[@ishwarsalunke1838]

Its great sir lovely

[@DevilMonk]

I was searching for a good statistics course i started like 5 courses and didn't like them but krish makes everything so simple and informative its absolutely amassing

[@junaidrizvi9884]

THANKS KRISH, SHAB-ba-Khair.

[@Consciousness382]

Beyond words.. Thankuu Krish, enjoyed a lot.

[@yogeshwarir3789]

Super sir... really u r doing good work and make others get confident.. also ur handwriting is superb

[@shanakamadhuranga]

This is a greate session Krish... Thanks for your effeort.

[@kuldeepkevat-u3u]

awesome krish really its wonderfull. your free classes is diwali gift for me. thanks again

[@kanishkkunal1326]

Good 1st day session.

[@vishallakhera6295]

Great work

[@punitsalwey7178]

Hey Krish, I want to learn statistics, not particularly for data science, and I find these videos very helpful. Can you please tell me where to access the notes of these videos?

[@maruthiprasad8184]

Thank you very much for your valuable knowledge sharing. Great job.

[@painKuro01]

Ur a godsend for BCA students

[@raghavsharma6430]

amazing video krish!!

[@sabbirbasunia2813]

Beautiful sir ♥️🥰

[@mohitvenkatasaimadala6094]

Hello sir(@krish Naik), Just now watched this video. Before watching this i am scared of statistics, after watching i got confidence that i can learn stats with ease. I think this playlist is my one stop destination for learning 📈stats in data science domain 📊. Thank you 🙏 and kubos🙋‍♂🙋‍♂ to your work sir...................

[@ruchamali]

you are the great teacher

[@fatishafaat2674]

superb lecture

[@tejeshivsn632]

Variable Measuring Scale: 1. Nominal: Numeric or Categorical 2. Ordinal: Numeric or Categorical and has order. Value does not matter. Eg: Military ranks, Class ranks. 3. Interval: Numeric or Categorical, it has an order, it has value, '0' absolute zero point not present. Eg: Fahrenheit temperature. There can be 95F and 100 F temperatures. The value of the difference between 80 and 85 is the same as the difference between 90 and 95. 0 F does not represent any meaning. 4. Ratio: Numeric or Categorical, Order matters, Value matters, Has absolute zero point. Eg: Kelvin scale. Having 0 K is having the lowest energy of water. The difference between the 2 temperatures also matters. Each temperature has its value. Some other examples: Customer satisfaction: satisfied, very satisfied, somewhat satisfied, somewhat unsatisfied -> Ordinal Hat, Shirt, Shoes, Pant -> Nominal City of birth -> Nominal Income -> Ratio GPA -> Interval Happy learning!! Thanks, Krish for the video.

[@mohamedfaalil]

Great session sir

[@vasanthalakshmi7824]

It is a wonderful stat playlist...this is what I was looking for the past month but I didn't get any precise content of stats...Thank you very much Krish for this amazing work by you

[@narendrapatnaik1154]

thanyouuu sir for saying we are amazing

[@amitgoswami7856]

nice explanation

[@lokeshmadiga6215]

Thank you Krish

[@rajapratappedapudi]

After watching all statistics 7-day live sessions and now I have got so much confidence in stats, and I am very sure that I could learn data science subject. The way you teach is very clear and absolutely very easy to understand which I didn't find in my university. A Big Thanks to you Krish Naik ji for your great effort to help me and many students with your knowledge to shine their future and it is much appreciated. 🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏

[@Akanksha-Tiwari2702]

Thank you Sir

[@roshniart163]

Good afternoon sir

[@victor75570]

Just the topic I was waiting for Krish. Thanks for sharing your knowledge with the data science community on youtube. You are the real MVP.

[@SusobhanDas]

Thanks

[@riturajgupta7926]

Please continue this series sir

[@MuhammadAhmed-vl5lq]

Loving it

[@kabbasoldji3816]

Thank you sir 😍

[@royalblue585]

Great Sir. Absolutely loved it. ❤️❤️❤️

[@pervysage_jiraiyaa]

Thanks.