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A question previously sought recommendations for textbooks on mathematical statistics

Does anyone know of any good online video lectures on mathematical statistics? The closest that I've found are:

UPDATE: A number of the suggestions mentioned below are good statistics-101 type videos. However, I'm specifically wondering whether there are any videos that provide a rigorous mathematical presentation of statistics. i.e., videos that might accompany a course that use a textbook mentioned in this discussion on mathoverflow

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Should be community wiki. –  mbq Jul 22 '10 at 11:21
    
Just noticed this related question: stackoverflow.com/questions/570029/… –  Jeromy Anglim Aug 7 '10 at 8:36
    
for more stats 101 videos, see: stats.stackexchange.com/questions/1761/… –  Jeromy Anglim Aug 17 '10 at 13:54
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20 Answers

See Videos on data analysis using R on Jeromy Anglim's blog. There are many links at that page and he updates it. He has another post with many links to videos on probability and statistics as well as linear algebra and calculus.

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There is one called Math and probability for life sciences, but I haven't followed it so I can't tell you if its good or not.

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I have watched all of those videos. It's a very good introduction to probability and counting. –  George Dontas Jul 27 '10 at 6:12
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I do not know at what level you want the videos to be but I have heard good things about Khan's Academy: http://www.khanacademy.org/#Statistics

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This site from Ecole normal Supérieure de Paris contains a lot of very interesting video

http://www.diffusion.ens.fr/index.php?res=themes&idtheme=30

I greatly encourage you to visit this site !!

Among other you will find there all video presentation from the conference "Mathematical Foundations of Learning Theory" that held in 2006.

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Many of the Berkeley introductory statistics courses are available online (and on iTunes). Here's an example: Stats 2. You can find more here.

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There is a new resources forming these days for talks about R:

http://www.r-bloggers.com/RUG/

Compiled by the organizers of "R Users Groups" around the world (right now, mainly around the States).

It is a new project (just a few weeks old), but already got good content on it, and good people wanting to take part in it. alt text

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There is a series of Google Tech Talk videos called Stats 202 - Statistical Aspects of Data Mining

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The folks at SLAC put videos of their lecture series online. Given that their audience is mostly physicists, they tend to be fairly mathematical.

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Yes, I now remember looking at one or two of these videos a few years back. They are quite mathematical. –  Jeromy Anglim Aug 9 '10 at 6:33
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There are a bunch of helpful video tutorials on basic statistics & data mining with R and Weka at SentimentMining.net.

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Besides that fact that the former link wasn't really related to mathematical statistics, the latter one is neither: "Data Mining with STATISTICA Video Series" - youtube.com/user/StatSoft#g/c/B804A810436AFB03 –  fbahr Sep 23 '10 at 14:00
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I found the 'Probability Primer' Lectures very useful and informative :

A series of videos giving an introduction to some of the basic definitions, notation, and concepts one would encounter in a 1st year graduate probability course.

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+1 Thanks for sharing. These lectures look really useful; I see that the author also has a set of other videos on machine learning and information theory: youtube.com/user/mathematicalmonk/videos?view=pl –  Jeromy Anglim Dec 15 '11 at 0:14
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MIT Open Courseware Discrete Stochastic Processes

Discrete stochastic processes are essentially probabilistic systems that evolve in time via random changes occurring at discrete fixed or random intervals. This course aims to help students acquire both the mathematical principles and the intuition necessary to create, analyze, and understand insightful models for a broad range of these processes. The range of areas for which discrete stochastic-process models are useful is constantly expanding, and includes many applications in engineering, physics, biology, operations research and finance.

The course includes videos, practice questions, slides, and an extensive set of notes.

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I am currently watching linear algebra lessons from MIT open-courseware when I get a chance. Also differential equations are on my to-do list. Although neither are directly related to statistics, but each has obvious extensions to a variety of statistical analysis. –  Andy W Aug 21 '12 at 1:49
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UCCS mathematics video archive has archived videos from a range of courses in mathematics. Several subjects called Mathematical Statistics I and Mathematical Statistics II are available. The main site requires a free registration to access.

Slightly more accessible are the videos for a subset of the courses on the UCCS MathOnline YouTube page. Two instances of this are as follows. The lecture style often involves Dr. Morrow working through problems on the whiteboard.

Linear Models

Taught by Dr. Greg Morrow, Math 483 from UCCS. Methods and results of linear algebra are developed to formulate and study a fundamental and widely applied area of statistics. Topics include generalized inverses, multivariate normal distribution and the general linear model. Applications focus on model building, design models, and computing methods. The Statistical Analysis System (software) is introduced as a tool for doing computations.

Course info: Seems to use Introduction to Linear Regression by Montgomery, Peck, and Vining.

Mathematical Statistics 1

Greg Morrow's Math 481 course from Math Online at the University of Colorado in Colorado Springs Course Description: Exponential, Beta, Gamma, Student, Fisher and Chi-square distributions are covered in this course, along with joint and conditional distributions, moment generating techniques, transformations of random variables and vectors.

  • Course info
  • Syllabus from one year
  • Mathematical Statistics and Data Analysis, 3rd ed., by John A. Rice.
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An introductory set of statistics lectures with a voice over a slide presentation.

http://www.online.math.uh.edu/Math2311/index.htm

The lecture series is elementary, but I like how the lecturer communicates clearly and shows how to speak the formulas encountered in statistics.

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Opinionated Lessons in Statistics

http://wiki.opinionatedlessons.org/coursewiki/index.php/OpinionatedLessons.org/

Around 50 videos on statistics by Professor William H. Press of the University of Texas at Austin. Each video is around 10 to 30 minutes long. A number of more advanced topics are coverd such as mixture models, EM methods, MCMC, PCA, and more.

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I just came across this website, CensusAtSchool -- Informal inference. Maybe worth looking at the videos and handouts...

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Years ago the ASA video taped workshop /short courses on special topics such as time series and survival analysis and categorical data analysis. They were available for chapters to rent. You might check to see what they have. Short courses at the jSM were occasionally video taped. I don't know if general math stat courses are available.

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Bookmark http://www.edxonline.org, it's bound to have all the math videos you could wish for. I believe they are hoping to launch this fall.

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Well, I don't why you want to find some vedios about mathematics. Actually, in my opinion, in order to learn the mathematical background thoroughly, you have to spend a lot of time on reading books related to it. You have to derive every theorem rigorously. So all in all, what I want to say is that, maybe watching vedios about mathematics wouldn't help you a lot, probably you should borrow some books like Mathematical Statistics, Asymptotic Theory, and things like that and read them carefully. Only in this way can you gain solid understanding of the mathematics behind statistics.

Good for you! And I'd like to discuss with you about some difficult problems.

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I think learning mathematics is facilitated by a combination of watching presentations, reading mathematical materials, and solving mathematical problems. This is the standard model in classrooms and university settings, and I think there is good reason for that. The question does not imply that you should avoid reading books and doing problems. –  Jeromy Anglim Aug 21 '12 at 1:14
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