Statistics And Probability Tutorial | Statistics And Probability for Data Science | Edureka
Вставка
- Опубліковано 5 лип 2024
- 🔥 Data Science Certification using R (Use Code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎"): www.edureka.co/data-science
This session on Statistics And Probability will cover all the fundamentals of stats and probability along with a practical demonstration in the R language. The following topics are covered in this session:
3:23 What Is Data?
4:17 Categories Of Data
9:01 What Is Statistics?
11:20 Basic Terminologies In Statistics
12:35 Sampling Techniques
17:46 Types Of Statistics
20:22 Descriptive Statistics
21:25 Measures Of Centre
25:40 Measures Of Spread
32:06 Information Gain & Entropy
44:13 Confusion Matrix
49:00 Descriptive Statistics Demo
53:09 Probability
55:33 Terminologies In Probability
57:46 Probability Distribution
1:03:00 Types Of Probability
1:10:00 Bayes' Theorem
1:15:34 Inferential Statistics
1:16:09 Point Estimation
1:19:05 Interval Estimation
1:22:23 Margin Of Error
1:22:57 Estimating Level Of Confidence
1:26:25 Hypothesis Testing
1:30:25 Inferential Statistics Demo
Blog Series: bit.ly/data-science-blogs
Data Science Training Playlist: bit.ly/data-science-playlist
- - - - - - - - - - - - - - - - -
Subscribe to our channel to get video updates. Hit the subscribe button above: goo.gl/6ohpTV
Instagram: / edureka_learning
Facebook: / edurekain
Twitter: / edurekain
LinkedIn: / edureka
- - - - - - - - - - - - - - - - -
About the Course
Edureka's Data Science course will cover the whole data lifecycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modeling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities.
- - - - - - - - - - - - - -
Why Learn Data Science?
Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework.
After the completion of the Data Science course, you should be able to:
1. Gain insight into the 'Roles' played by a Data Scientist
2. Analyze Big Data using R, Hadoop and Machine Learning
3. Understand the Data Analysis Life Cycle
4. Work with different data formats like XML, CSV and SAS, SPSS, etc.
5. Learn tools and techniques for data transformation
6. Understand Data Mining techniques and their implementation
7. Analyze data using machine learning algorithms in R
8. Work with Hadoop Mappers and Reducers to analyze data
9. Implement various Machine Learning Algorithms in Apache Mahout
10. Gain insight into data visualization and optimization techniques
11. Explore the parallel processing feature in R
- - - - - - - - - - - - - -
Who should go for this course?
The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course:
1. Developers aspiring to be a 'Data Scientist'
2. Analytics Managers who are leading a team of analysts
3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics
4. Business Analysts who want to understand Machine Learning (ML) Techniques
5. Information Architects who want to gain expertise in Predictive Analytics
6. 'R' professionals who want to captivate and analyze Big Data
7. Hadoop Professionals who want to learn R and ML techniques
8. Analysts wanting to understand Data Science methodologies.
For online Data Science training, please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information.
Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For Data Science Training and Certification, Visit our Website: bit.ly/37q65Oc
Great Explanation on the IG and Entropy part. Thanks for that!
Thank you Zulekha from EDUREKA.
explanation was very good, thank you
Excellent explanation! Thank you.
So far the best source available on web to brush up stats concepts for Data Science.
Cheers to Edureka & Zulaikha.
Thank you for your appreciation. Do subscribe to our channel and stay connected with us. Cheers :)
thank you so much for sharing this video😇😇
Excellent explanation, thank you for making such a video which explains the concepts so clearly
Thank you for appreciating our efforts. Do subscribe to our channel and stay connected with us. Cheers!
❤ Great job Edureka !
Amazing coverage of statistics.
Please make a video over mathematics required in data science. I am very confused like what to cover and how much to cover in mathematics.
Thanks for the compliment, Abhishek! We're glad you liked it. We shall forward your request to the content team.
THANKS FOR THE QUALITY VIDEO AND MINE OF INFORMATION 👍🏼
Thank you so much for making video on complete probability , statistics in one video
You are most welcome 😊 Glad it was helpful!
thanks a lot, i learned a lot i did not know
Thank you for this
Good presentation thx
Thx for sharing
INTRESTING & KNOWLEDGEFUL and stepping stone to SUCCESS.
Thank you for your review : ) We are glad that you found our videos /contents useful . We are also trying our best to further fulfill your requirements and enhance your expirence :) Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )
This was really helpful!! Thanks for uploading!!
You are welcome👍
We are glad we could help. Do subscribe to our channel to stay posted on upcoming tutorials: ua-cam.com/users/edurekaIN.
It is humble request if you will share pdf of this video ?
You people have done a great, amazing work
Thanks
This is Pure Gold
Thank You 😊 Glad you liked it!!
Thank you Zulekha and Edureka
Thanks EDUREKA.. .. .. .. ..
superb!!!
The way she is teaching 👌
Awesome, it clear my all doubt🤟
Thank you so much : ) We are glad to be a part of your learning journey. Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )
concise and informative...thank u so much...Edureka team.
Hey Narender, thanks for the compliment. Do subscribe to our channel and stay connected with us. Cheers!
@@edurekaIN already subscribbed..
Good presentation and content
Awesome thanks
MAM explained it very nicely
Informative video
Amazing Video! I really tried answering the question for Bayes Theorem but couldnt figure it out... Could you help me out please?
Thanks a lot.. Mam and Edureka team.. Very good content.. And.. Nice explaination by mam..
You are welcome Shivam. Don't forget to Subscribe our channel.
I had been trying to understand IG and entropy but never got such a simple explanation. Thanks very much Edureka team :)🙂🙂
Thank you for your review : ) We are glad that you found our videos /contents useful . We are also trying our best to further fulfill your requirements and enhance your expirence :) Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )
Very nice explanation
Your voice is really good. It is so sweet just like needed for the students to capture their attention on the subject matter
Thanks.
😇😇😇
Sure 😇😇😇
Very nice explanation...thank you...
Hi : ) We really are glad to hear this ! Truly feels good that our team is delivering and making your learning easier :) Keep learning with us .Stay connected with our channel and team :) . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )
Superb session, Thanks to Edureka and trainer, crisp precise and well modulated - where can I get a copy of this presentation for reference?
Hi ! Glad you liked it ! We are glad to have learners like you .Drop your mail id in the comment section for us to share the data sheets or source codes :) Do subscribe our channel and hit that bell icon to never miss an video from our channel .
Nice vedio.
Thank you so much mam
it goes fast although, but good teaching
Mam I am new to learn data science what is the sequence of concept which I have to follow and is any prerequisite required before this
Or if I randomly learning anything for this is good or bad ???
Please mam ????
superb!!well Explanation
Glad it was helpful!
thank you for this wonderful video, but may i ask what reference you use?
Hi Ahmad, our references are collective and if you wish to use them for your practise. Kindly drop in your respective email id and we will share it to you. Cheers :)
nice work
*35:05*
Thank you so much
You are welcome👍
Awesome session 👍
Thank you so much for your review on our channel Great to hear that Edureka is helping you learn better . We’ll strive to make even better learning contents/courses in the future ! Do subscribe the channel for more updates : )
Good Evening ma'am thank you for awesome video and Your voice like Madhuri Dixit. lovely voice.
Hey:) Thank you so much for your sweet words :) Really means a lot ! Glad to know that our content/courses is making you learn better :) Our team is striving hard to give the best content. Keep learning with us -Team Edureka :) Don't forget to like the video and share it with maximum people:) Do subscribe the channel:)
Thanks for the lecture
Most welcome!
Please upload video about confidence interval
Hi Siddhant, we have considered your request and our team will definitely come up with an exclusive tutorial to guide you. Meanwhile, do subscribe to our channel and stay tuned. Cheers :)
@@edurekaIN thank you
Amazing training! Lol the bowl sounded like bowel....regardless best training!
We are very glad to hear that your a learning well with our contents 😊 continue to learn with us and don't forget to subscribe our channel so that you don't miss any updates !
Where can I find the theoretical material for the same?
Hi please share your mail id to share the data sheet :) We'll Update you soon ! Do Subscribe the channel to keep updated
why are true positive and false negatives considered as classification?
A true positive is an outcome where the model correctly predicts the positive class. Similarly, a true negative is an outcome where the model correctly predicts the negative class.
A false positive is an outcome where the model incorrectly predicts the positive class. And a false negative is an outcome where the model incorrectly predicts the negative class.
At around 7:58 minutes, you have said that Spam or not Spam is considered as Discrete or Categorical .. so does it not come under Nominal Data in Qualitative??
It is Quantitative.
solution of probability question is 5/36 i think
I love your voice 😍❤
so nice of you
excellent video. can i get the material or notes of this topic. I am student
Good to know our contents and videos are helping you learn better . We are glad to have you with us ! Please share your mail id to send the data sheets to help you learn better :) Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )
Your voice is cherry on cake. Outstanding .
could you share this slide please?
Hi, unfortunately we do not share the presentations used in our tutorial. On the bright side, here is a link: bit.ly/39ZZ7lh to help you. Happy learning :)
i like to
Great
Thank you so much for your review on our channel Great to hear that Edureka is helping you learn better . We’ll strive to make even better learning contents/courses in the future ! Do subscribe the channel for more updates : )
pdf provide kra do please
Good to know your learning with edureka :) please share your mail id to share the data sheet! We'll Update you soon !
can you please send me the ppt ?
Hi ! Good to know that our videos are helping you to learn better :) Please share your mail id to share the data sheets :)We’ll update you soon . Do subscribe the channel for more updates : )
Please in hindi
Hi, we are working on your request. The video will be out soon. Here's a link to our Hindi channel: ua-cam.com/channels/ywyZ4r4FTKExrPl9rf-ggw.html Do subscribe and stay tuned for future updates. Cheers!
answer is 4/5