Resources on Advanced Statistics & Probability as per ChatGPT

Here’s a list of some excellent resources across various formats—books, YouTube channels, and blogs—that cover advanced statistics and probability theories:

Books:

1. “Introduction to Probability” by Dimitri P. Bertsekas and John N. Tsitsiklis

– A comprehensive introduction to probability, available for free in PDF form on MIT’s OpenCourseWare.

– [Link to PDF](https://athenasc.com/probbook.html)

2. “Think Stats” by Allen B. Downey

– This book focuses on applying statistics to real-world data, with practical examples using Python.

– [Link to PDF](https://greenteapress.com/wp/think-stats-2e/)

3. “The Elements of Statistical Learning” by Trevor Hastie, Robert Tibshirani, and Jerome Friedman

– A highly regarded book on statistical learning, offering a deep dive into many advanced topics.

– [Link to PDF](https://web.stanford.edu/~hastie/ElemStatLearn/)

4. “All of Statistics: A Concise Course in Statistical Inference” by Larry Wasserman

– A great resource that covers both basic and advanced topics in statistics.

– [Link to PDF](https://www.stat.cmu.edu/~larry/all-of-statistics/)

5. “Introduction to Statistical Thought” by Michael Lavine

– This book covers the foundations of statistical inference and is available for free online.

– [Link to PDF](https://www.math.umass.edu/~lavine/Book/book.html)

YouTube Channels:

1. MIT OpenCourseWare – Probability and Statistics

– Features lectures from MIT’s undergraduate and graduate courses, including advanced topics in probability and statistics.

– [MIT OCW YouTube Channel](https://www.youtube.com/user/MIT)

2. Khan Academy

– Although mostly known for basic statistics, Khan Academy also offers more advanced courses in probability and statistical inference.

– [Khan Academy – Probability & Statistics](https://www.youtube.com/user/khanacademy)

3. StatQuest with Josh Starmer

– Excellent channel that breaks down complex statistical concepts into easily understandable segments, including advanced topics.

– [StatQuest YouTube Channel](https://www.youtube.com/user/joshstarmer)

4. Brilliant.org

– While Brilliant offers paid content, their YouTube channel provides free videos covering advanced mathematical concepts, including probability and statistics.

– [Brilliant.org YouTube Channel](https://www.youtube.com/c/Brilliantorg)

5. Harvard University – STAT110 (Probability)

– Lectures from Harvard’s popular STAT110 course, taught by Professor Joe Blitzstein, covering probability theory in depth.

– [Harvard University – STAT110 YouTube Channel](https://www.youtube.com/playlist?list=PL2SOU6wwxB0v1kQTpqpuuGIjJRWJaFfeH)

Blogs and Online Courses:

1. Cross Validated (Stack Exchange)

– A Q&A site specifically for statistics, probability, and data science. It’s a great place to see advanced problems discussed in depth.

– [Cross Validated](https://stats.stackexchange.com/)

2. OpenIntro

– Offers free textbooks, labs, and resources on statistics, including advanced topics.

– [OpenIntro](https://www.openintro.org/)

3. Towards Data Science (Medium)

– A popular blog on Medium with numerous articles on advanced statistics, probability, and their applications in data science.

– [Towards Data Science](https://towardsdatascience.com/)

4. DataCamp Community

– While DataCamp offers paid courses, their blog has free articles and tutorials on advanced statistical methods.

– [DataCamp Community](https://www.datacamp.com/community)

5. Probability and Statistics EBook

– An online resource that provides detailed explanations of advanced topics in probability and statistics.

– [Probability and Statistics EBook](http://www.probabilitycourse.com/)

MOOCs and Online Lectures:

1. Coursera – Statistical Learning by Stanford University

– A free course that covers statistical learning, based on the book “The Elements of Statistical Learning.”

– [Coursera – Statistical Learning](https://www.coursera.org/learn/statistical-learning)

2. edX – Probability: The Science of Uncertainty and Data by MIT

– A free course that dives deep into probability theory and applications.

– [edX – MIT Probability Course](https://www.edx.org/course/probability-the-science-of-uncertainty-and-data)

3. Harvard Online Learning – Data Science: Probability

– Part of Harvard’s Data Science Professional Certificate, this course is available for free auditing.

– [Harvard – Data Science: Probability](https://online-learning.harvard.edu/course/data-science-probability)

These resources cover a broad range of advanced topics in probability and statistics, and they offer various levels of depth, from introductory overviews to rigorous academic treatments.

By Neil Harwani

Interested in movies, music, history, computer science, software, engineering and technology

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