Statistics 110: Probability
by Harvard University
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|1||Syllabus||--||--||Free||View In iTunes|
|2||Lecture 1: Probability and Counting||--||46:29||Free||View In iTunes|
|3||Lecture 2: Story Proofs, Axioms of Probability||--||45:40||Free||View In iTunes|
|4||Strategic Practice and Homework 1||--||--||Free||View In iTunes|
|5||Lecture 3: Birthday Problem, Properties of Probability||--||48:54||Free||View In iTunes|
|6||Lecture 4: Conditional Probability||--||49:45||Free||View In iTunes|
|7||Lecture 5: Conditioning Continued, Law of Total Probability||--||50:01||Free||View In iTunes|
|8||Lecture 6: Monty Hall, Simpson's Paradox||--||49:00||Free||View In iTunes|
|9||Lecture 7: Gambler's Ruin and Random Variables||--||51:45||Free||View In iTunes|
|10||Lecture 8: Random Variables and Their Distributions||--||50:23||Free||View In iTunes|
|11||Strategic Practice and Homework 3||--||--||Free||View In iTunes|
|12||Lecture 9: Expectation, Indicator Random Variables, Linearity||--||50:22||Free||View In iTunes|
|13||Lecture 10: Expectation Continued||--||50:10||Free||View In iTunes|
|14||Lecture 11: The Poisson Distribution||--||42:46||Free||View In iTunes|
|15||Strategic Practice and Homework 4||--||--||Free||View In iTunes|
|16||Lecture 12: Discrete vs. Continuous, the Uniform||--||49:56||Free||View In iTunes|
|17||Lecture 13: Normal Distribution||--||51:09||Free||View In iTunes|
|18||Lecture 14: Location, Scale and LOTUS||--||48:55||Free||View In iTunes|
|19||Lecture 15: Midterm Review||--||38:11||Free||View In iTunes|
|20||Midterm Review||--||--||Free||View In iTunes|
|21||Midterm Exam||--||--||Free||View In iTunes|
|22||Lecture 16: Exponential Distribution||--||18:19||Free||View In iTunes|
|23||Lecture 17: Moment Generating Functions||--||50:44||Free||View In iTunes|
|24||Lecture 18: MGFs Continued||--||49:40||Free||View In iTunes|
|25||Strategic Practice and Homework 6||--||--||Free||View In iTunes|
|26||Lecture 19: Joint, Conditional, and Marginal Distributions||--||50:09||Free||View In iTunes|
|27||Lecture 20: Multinomial and Cauchy||--||48:59||Free||View In iTunes|
|28||Strategic Practice and Homework 7||--||--||Free||View In iTunes|
|29||Lecture 21: Covariance and Correlation||--||49:26||Free||View In iTunes|
|30||Lecture 22: Transformations and Convolutions||--||47:46||Free||View In iTunes|
|31||Strategic Practice and Homework 8||--||--||Free||View In iTunes|
|32||Lecture 23: Beta Distribution||--||49:48||Free||View In iTunes|
|33||Lecture 24: Gamma Distribution and Poisson Process||--||48:49||Free||View In iTunes|
|34||Lecture 25: Order Statistics and Conditional Expectation||--||48:15||Free||View In iTunes|
|35||Lecture 26: Conditional Expectation Continued||--||49:52||Free||View In iTunes|
|36||Strategic Practice and Homework 9||--||--||Free||View In iTunes|
|37||Lecture 27: Conditional Expectation Given an R.V.||--||50:33||Free||View In iTunes|
|38||Lecture 28: Inequalities||--||47:29||Free||View In iTunes|
|39||Strategic Practice and Homework 10||--||--||Free||View In iTunes|
|40||Lecture 29: Law of Large Numbers and Central Limit Theorem||--||49:48||Free||View In iTunes|
|41||Lecture 30: Chi-Square, Student-t, Multivariate Normal||--||47:27||Free||View In iTunes|
|42||Lecture 31: Markov Chains||--||46:38||Free||View In iTunes|
|43||Lecture 32: Markov Chains Continued||--||48:23||Free||View In iTunes|
|44||Lecture 33: Markov Chains Continued Further||--||47:00||Free||View In iTunes|
|45||Strategic Practice and Homework 11||--||--||Free||View In iTunes|
|46||Lecture 34: A Look Ahead||--||36:58||Free||View In iTunes|
|47||Final Review||--||--||Free||View In iTunes|
|48||Final Exam||--||--||Free||View In iTunes|
|49||Strategic Practice and Homework 5||--||--||Free||View In iTunes|
|50||Math Review Handout||--||--||Free||View In iTunes|
|51||Markov Chains Handout||--||--||Free||View In iTunes|
|52||Strategic Practice and Homework 2||--||--||Free||View In iTunes|
Joe is the best!!!
Joe's teaching skills exceeds other statistics professors significantly, so do his jokes.
Trust me, my friend. I took this course two years ago, and you are so lucky could be mentored by the most brilliant professor in the world! And it is free!
For what you can learn from Stat 110, there is no better!
Professor Blitzstein is just the best at what he does - for the level of difficulty and complexity of the material, it's surprisingly well presented and easy to understand! Most professors of Blitzstein's caliber fail to adequately present and teach the material because so many of the concepts we find difficult may be trivial for them, but professor Blitzstein has a way with painting pictures and making stories that make even the toughest distributions, probability functions, theorems, etc. (including ways of solving notoriously difficult Putnam Competition questions) make so much sense! Job interviews - no problem anymore!
Good except for way these videos are recorded.
Everything in this course is nice. The professor is really good and he explains things well. However, the only thing I hate so much about this course that makes me stop watching it is that the recorder always zoomed in to the professor's face. That means I cannot see anything he wrote on the blackboard and it's pretty annoying to constantly go back and watch what he just wrote again. Seriously, the recorder can zoom out a bit to make us able to see the whole board, because the text is big anyway. Please fix this next time the recorder.