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Credits : Joe Blitzstein stat110 - Professor of Statistics at Harvard, Instructor of Harvard's Stat 110 course (Probability).
Explore these recommended books to enhance your understanding of Probability and Statistics:
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"Introduction to Probability" by Joe Blitzstein and Jessica Hwang - Stat110 course book; An introductory textbook that covers a wide range of probability concepts.
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"A FIRST COURSE IN PROBABILITY" by Sheldon Ross Most appropriate book for Graduate level and Gate preparation
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"All of Statistics: A Concise Course in Statistical Inference" by Larry Wasserman A comprehensive resource for statistical theory and its applications.
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"Introduction to probability, statistics, and random processes" by H. Pishro-Nik It is an open access peer-reviewed textbook intended for undergraduate as well as first-year graduate level courses on the subject. This probability textbook can be used by both students and practitioners in engineering and mathematics
Course to deepen your knowledge of Probability and Statistics:
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Probability for Computer Science, IIT Kanpur by Prof. Nitin Saxena IIT K,This is a crash course to introduce the concept of probability formally; and exhibit its applications in computer science, combinatorics, and algorithms. Excellent Assignments with MCQs
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Stat110 (Probability) taught at Harvard University by Joe Blitzstein: Lecture videos, review materials, and over 250 practice problems with detailed solutions are provided. This course is an introduction to probability as a language and set of tools for understanding statistics, science, risk, and randomness.
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Statistics and Probability | Khan Academy The course looks vast, but upon deeper inspection, it seems like a mashup of undergraduate probability, including random variables and statistics. The probability portion is very similar to the engineering mathematics syllabus of the gate; the statistics part is a bit of addition that needs to be studied and contains primarily hypothesis testing.
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Electrical - Probability Foundation for Electrical Engineers Probability Foundation for Electrical Engineers by Dr. Krishna Jagannathan,Department of Electrical Engineering,IIT Madras.
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MIT RES.6-012 Introduction to Probability, Spring 2018 Instructor: John Tsitsiklis, Patrick Jaillet; The tools of probability theory, and of the related field of statistical inference, are the keys for being able to analyze and make sense of data. These tools underlie important advances in many fields, from the basic sciences to engineering and management.
Review these comprehensive notes to reinforce your grasp of Probability and Statistics:
- Probability Review An guide that explains different types of probability distributions and covers pre-requisites for ML. From COL774: Machine Learning (IIT D) by Prof. Parag Singla
- Multivariate Gaussians Review From COL774: Machine Learning (IIT D) by Prof. Parag Singla
For the visual learners:
- Central Limit Theorem : 3Blue1Brown Why and how of the "Central Limit Theorem" through intuition and visualisation.
- Bayes Theorem: 3Blue1Brown Intuitive understanding of Bayes Theorem, the foundation for Bayesian Statistics.
Read insightful articles on Probability and Statistics to gain additional insights:
- Probability and Statistics : Geeks For Geeks Detailed articles covering fundamental concepts, formulas, and examples.
Test your knowledge and skills with these practice problems:
- Probability and Statistics Practice Problems A collection of practice problems ranging from basic to advanced concepts. Previous year Gate Questions
- Assignment Questions from NPTEL Course: MCQs 🌟 🌟 Important
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