# playlist (click the video's upper-left icon)
source: Centre International de Rencontres Mathématiques 2015年8月5日
01 Martin Wainwright: Privacy and statistical minimax: quantitative tradeoffs 49:30
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Recording during the thematic meeting: "Meeting on mathematical statistics" the December 10, 2013 at the Centre International de Rencontres Mathématiques (Marseille, France)
Film maker: Guillaume Hennenfent
Showing posts with label A. (subjects)-Engineering & Physical Sciences-Mathematics-Probability and Statistics. Show all posts
Showing posts with label A. (subjects)-Engineering & Physical Sciences-Mathematics-Probability and Statistics. Show all posts
2017-08-24
2017-04-14
Probability and Statistics: an introduction by Norman J. Wildberger
# click the upper-left icon to select videos from the playlist
source: njwildberger 2013年9月28日
This is the first lecture of a short course introducing probability and statistics, meant for an advanced first year undergraduate class. The course will be about 8 lectures long, and will go from basic sets, counting, probability and odds, to probability measures, conditional probabilities, Bayes rule, random variables, probability distributions (discrete and continuous), mean, variance, Binomial, Poisson, normal distributions, and perhaps some words in the direction of the Central Limit Theorem. We will not discuss inference in this course, so it is a rather limited, specific introduction to the subject.
In this lecture I review some basic notation and terminology for sets, including operations and rules, the Inclusion/Exclusion principle and partitions; together with some basic facts about functions.
My research papers can be found at my Research Gate page, at https://www.researchgate.net/profile/.... I also have a blog at http://njwildberger.com/, where I will discuss lots of foundational issues, along with other things, and you can check out my webpages at http://web.maths.unsw.edu.au/~norman/. Of course if you want to support all these bold initiatives, become a Patron of this Channel at https://www.patreon.com/njwildberger?... .
Probability and Statistics: an introduction
A brief introduction to Probability and Statistics. This short course will be aimed at advanced first year undergraduates, with good algebraic skills and some knowledge of calculus. We will discuss probabilities and odds, random variables, probability distributions (both discrete and continuous), for example the Binomial, Poisson and normal distributions, mean and variance and mention the Central Limit Theorem.
1: Review of sets and functions 51:26
2: Basic Counting and Probability 49:53
3: Probabiilty spaces, events and conditional probabilities 49:22
4: Total probability, Bayes' rule and tree diagrams 52:09
5: Random variables, means, variance and standard deviations 53:09
6: Binomial and geometric distributions 52:22
7: The sign rule and continuous probability distributions 50:15
8: The normal distribution 48:24
source: njwildberger 2013年9月28日
This is the first lecture of a short course introducing probability and statistics, meant for an advanced first year undergraduate class. The course will be about 8 lectures long, and will go from basic sets, counting, probability and odds, to probability measures, conditional probabilities, Bayes rule, random variables, probability distributions (discrete and continuous), mean, variance, Binomial, Poisson, normal distributions, and perhaps some words in the direction of the Central Limit Theorem. We will not discuss inference in this course, so it is a rather limited, specific introduction to the subject.
In this lecture I review some basic notation and terminology for sets, including operations and rules, the Inclusion/Exclusion principle and partitions; together with some basic facts about functions.
My research papers can be found at my Research Gate page, at https://www.researchgate.net/profile/.... I also have a blog at http://njwildberger.com/, where I will discuss lots of foundational issues, along with other things, and you can check out my webpages at http://web.maths.unsw.edu.au/~norman/. Of course if you want to support all these bold initiatives, become a Patron of this Channel at https://www.patreon.com/njwildberger?... .
Probability and Statistics: an introduction
A brief introduction to Probability and Statistics. This short course will be aimed at advanced first year undergraduates, with good algebraic skills and some knowledge of calculus. We will discuss probabilities and odds, random variables, probability distributions (both discrete and continuous), for example the Binomial, Poisson and normal distributions, mean and variance and mention the Central Limit Theorem.
1: Review of sets and functions 51:26
2: Basic Counting and Probability 49:53
3: Probabiilty spaces, events and conditional probabilities 49:22
4: Total probability, Bayes' rule and tree diagrams 52:09
5: Random variables, means, variance and standard deviations 53:09
6: Binomial and geometric distributions 52:22
7: The sign rule and continuous probability distributions 50:15
8: The normal distribution 48:24
2017-02-10
Probability and Statistics by Mike Marks at ETSU
# click the up-left corner to select videos from the playlist
source: East Tennessee State University 2016年1月13日
Math 1530 Prob and Stats
MATH 1530 Introduction, pp 13 17 1:21:07
MATH 1530 pp 18 25 1:24:13
MATH 1530 pp 25 34, 47 1:24:42
MATH 1530 pp. 48-55 1:24:09
MATH 1530 pp 55 65, 75 1:21:33
MATH 1530 pp 76 84 1:23:07
MATH 1530 pp 85 92 1:21:51
MATH 1530 101 110 1:21:02
MATH 1530 pp 109 116, 127 130 1:23:45
MATH 1530 pp 131 137 1:21:52
MATH 1530 pp 138 150, 163 165 1:23:55
MATH 1530 PP 166 172, 203 206 1:21:35
MATH 1530 pp 207 213 1:21:46
MATH 1530 pp 213 218, 227 233 1:23:21
MATH 1530 pp 234 243, 277 280 1:23:53
MATH 1530 pp 281 288 1:21:47
MATH 1530 pp 289 294, 303 305 1:23:51
MATH 1530 pp 304-315 1:23:24
MATH 1530 pp 346 360 1:21:56
MATH 1530 pp 373 384 1:23:50
MATH 1530 pp 391 396 1:23:12
MATH 1530 pp 396 402 1:19:39
MATH 1530 pp 415 430, 517 518 1:22:02
MATH 1530 pp 456 471, 485 488 1:23:16
MATH 1530 pp 490 498, 577 594 1:21:53
MATH 1530 pp 518 527, 455 456 1:21:04
source: East Tennessee State University 2016年1月13日
Math 1530 Prob and Stats
MATH 1530 Introduction, pp 13 17 1:21:07
MATH 1530 pp 18 25 1:24:13
MATH 1530 pp 25 34, 47 1:24:42
MATH 1530 pp. 48-55 1:24:09
MATH 1530 pp 55 65, 75 1:21:33
MATH 1530 pp 76 84 1:23:07
MATH 1530 pp 85 92 1:21:51
MATH 1530 101 110 1:21:02
MATH 1530 pp 109 116, 127 130 1:23:45
MATH 1530 pp 131 137 1:21:52
MATH 1530 pp 138 150, 163 165 1:23:55
MATH 1530 PP 166 172, 203 206 1:21:35
MATH 1530 pp 207 213 1:21:46
MATH 1530 pp 213 218, 227 233 1:23:21
MATH 1530 pp 234 243, 277 280 1:23:53
MATH 1530 pp 281 288 1:21:47
MATH 1530 pp 289 294, 303 305 1:23:51
MATH 1530 pp 304-315 1:23:24
MATH 1530 pp 346 360 1:21:56
MATH 1530 pp 373 384 1:23:50
MATH 1530 pp 391 396 1:23:12
MATH 1530 pp 396 402 1:19:39
MATH 1530 pp 415 430, 517 518 1:22:02
MATH 1530 pp 456 471, 485 488 1:23:16
MATH 1530 pp 490 498, 577 594 1:21:53
MATH 1530 pp 518 527, 455 456 1:21:04
2016-10-20
Somesh Kumar: Probability and Statistics (IIT Kharagpur)
# playlist of the 40 videos (click the up-left corner of the video)
source: nptelhrd 2011年8月21日
Mathematics - Probability and Statistics by Dr.Somesh Kumar, Department of Mathematics, IIT Kharagpur. For more details on NPTEL visit http://nptel.iitm.ac.in
01 Algebra of Sets - I 54:32
02 Algebra of Sets - II 56:46
03 Introduction to Probability 56:55
04 Laws of Probability - I 54:21
05 Laws of Probability - II 57:53
06 Problems in Probability 58:20
07 Random Variables 54:42
08 Probability Distributions 58:31
09 Characteristics of Distributions 55:46
10 Special Distributions - I 56:01
11 Special Distributions - II 55:47
12 Special Distributions - III 57:06
18 Joint Distributions - I 54:44
13 Special Distributions - IV 57:00
14 Special Distributions - V 54:26
15 Special Distributions - VI 56:41
16 Special Distributions - VII 56:13
17 Function of a Random Variable 57:12
19 Joint Distributions - II 59:51
20 Joint Distributions - III 56:35
21 Joint Distributions - IV 54:20
22 Transformations of Random Vectors 56:45
23 Sampling Distributions - I 55:21
24 Sampling Distributions - II 59:28
25 Descriptive Statistics - I 56:26
26 Descriptive Statistics - II 59:26
27 Estimation - I 58:50
28 Estimation - II 56:03
29 Estimation - III 58:02
30 Estimation - IV 57:49
31 Estimation - V 55:12
32 Estimation - VI 56:30
33 Testing of Hypothesis - I 53:59
34 Testing of Hypothesis - II 54:19
35 Testing of Hypothesis - III 57:10
36 Testing of Hypothesis - IV 52:19
37 Testing of Hypothesis - V 54:18
38 Testing of Hypothesis - VI 55:36
39 Testing of Hypothesis VII 55:54
40 Testing of Hypothesis - VIII 56:24
source: nptelhrd 2011年8月21日
Mathematics - Probability and Statistics by Dr.Somesh Kumar, Department of Mathematics, IIT Kharagpur. For more details on NPTEL visit http://nptel.iitm.ac.in
01 Algebra of Sets - I 54:32
02 Algebra of Sets - II 56:46
03 Introduction to Probability 56:55
04 Laws of Probability - I 54:21
05 Laws of Probability - II 57:53
06 Problems in Probability 58:20
07 Random Variables 54:42
08 Probability Distributions 58:31
09 Characteristics of Distributions 55:46
10 Special Distributions - I 56:01
11 Special Distributions - II 55:47
12 Special Distributions - III 57:06
18 Joint Distributions - I 54:44
13 Special Distributions - IV 57:00
14 Special Distributions - V 54:26
15 Special Distributions - VI 56:41
16 Special Distributions - VII 56:13
17 Function of a Random Variable 57:12
19 Joint Distributions - II 59:51
20 Joint Distributions - III 56:35
21 Joint Distributions - IV 54:20
22 Transformations of Random Vectors 56:45
23 Sampling Distributions - I 55:21
24 Sampling Distributions - II 59:28
25 Descriptive Statistics - I 56:26
26 Descriptive Statistics - II 59:26
27 Estimation - I 58:50
28 Estimation - II 56:03
29 Estimation - III 58:02
30 Estimation - IV 57:49
31 Estimation - V 55:12
32 Estimation - VI 56:30
33 Testing of Hypothesis - I 53:59
34 Testing of Hypothesis - II 54:19
35 Testing of Hypothesis - III 57:10
36 Testing of Hypothesis - IV 52:19
37 Testing of Hypothesis - V 54:18
38 Testing of Hypothesis - VI 55:36
39 Testing of Hypothesis VII 55:54
40 Testing of Hypothesis - VIII 56:24
2015-11-05
Math 131A--Introduction to Probability and Statistics (Summer 2013)--Michael C. Cranston / UC Irvine
# automatic playing for the 17 videos (click the up-left corner for the list)
source: UCIrvineOCW 上次更新日期：2015年1月26日
UCI Math 131A: Introduction to Probability and Statistics (Summer 2013)
View the complete course: http://ocw.uci.edu/courses/math_131a_...
License: Creative Commons CC-BY-SA
Terms of Use: http://ocw.uci.edu/info
More courses at http://ocw.uci.edu
Description: UCI Math 131A is an introductory course covering basic principles of probability and statistical inference. Axiomatic definition of probability, random variables, probability distributions, expectation.
UC Irvine OpenCourseWare 0:22
Lecture 1. Probability 1:44:04
Lecture 2. Probability 1:12:42
Lecture 3. Random Variables 1:41:35
Lecture 4. Joint Distribution 1:39:13
Lecture 5. Expected Values 1:38:32
Lecture 6. Joint Distribution 1:39:56
Lecture 7. Limit Theorems 1:42:39
Lecture 8: Distributions from normal Distribution 1:32:55
Lecture 9. Conditional Probability 1:01:37
Lecture 10. Survey Sampling 1:35:35
Lecture 11. Estimation of Parameters 1:34:49
Lecture 12. Fitting of Probability Distributions 1:33:41
Lecture 13. Hypothesis Testing 1:42:14
Lecture 14. Random Sampling 1:37:15
Lecture 15. Simple Random Sampling 1:09:14
Lecture 16. Final Review 1:44:48
source: UCIrvineOCW 上次更新日期：2015年1月26日
UCI Math 131A: Introduction to Probability and Statistics (Summer 2013)
View the complete course: http://ocw.uci.edu/courses/math_131a_...
License: Creative Commons CC-BY-SA
Terms of Use: http://ocw.uci.edu/info
More courses at http://ocw.uci.edu
Description: UCI Math 131A is an introductory course covering basic principles of probability and statistical inference. Axiomatic definition of probability, random variables, probability distributions, expectation.
UC Irvine OpenCourseWare 0:22
Lecture 1. Probability 1:44:04
Lecture 2. Probability 1:12:42
Lecture 3. Random Variables 1:41:35
Lecture 4. Joint Distribution 1:39:13
Lecture 5. Expected Values 1:38:32
Lecture 6. Joint Distribution 1:39:56
Lecture 7. Limit Theorems 1:42:39
Lecture 8: Distributions from normal Distribution 1:32:55
Lecture 9. Conditional Probability 1:01:37
Lecture 10. Survey Sampling 1:35:35
Lecture 11. Estimation of Parameters 1:34:49
Lecture 12. Fitting of Probability Distributions 1:33:41
Lecture 13. Hypothesis Testing 1:42:14
Lecture 14. Random Sampling 1:37:15
Lecture 15. Simple Random Sampling 1:09:14
Lecture 16. Final Review 1:44:48
Math 131B--Introduction to Probability and Statistics (Summer 2013)--Michael C. Cranston / UC Irvine
# automatic playing for the 16 videos (click the up-left corner for the list)
source: UCIrvineOCW 上次更新日期：2015年1月26日
UCI Math 131B: Introduction to Probability and Statistics (Summer 2013)
View the complete course: http://ocw.uci.edu/courses/math_131b_...
License: Creative Commons CC-BY-SA
Terms of Use: http://ocw.uci.edu/info
More courses at http://ocw.uci.edu
Description: UCI Math 131B is an introductory course covering basic principles of probability and statistical inference. Point estimation, interval estimating, and testing hypotheses, Bayesian approaches to inference.
UC Irvine OpenCourseWare 0:22
Lecture 01. 1:44:39
Lecture 02. 1:34:01
Lecture 03. 1:37:19
Lecture 04. 1:39:28
Lecture 05. 1:41:11
Lecture 06. 1:31:32
Lecture 07. 1:29:05
Lecture 08. 1:15:21
Lecture 09. 1:40:59
Lecture 10. 1:41:36
Lecture 11. 1:32:37
Lecture 12. 1:32:02
Lecture 13. 1:38:45
Lecture 14. 1:39:25
Lecture 15. 1:37:54
source: UCIrvineOCW 上次更新日期：2015年1月26日
UCI Math 131B: Introduction to Probability and Statistics (Summer 2013)
View the complete course: http://ocw.uci.edu/courses/math_131b_...
License: Creative Commons CC-BY-SA
Terms of Use: http://ocw.uci.edu/info
More courses at http://ocw.uci.edu
Description: UCI Math 131B is an introductory course covering basic principles of probability and statistical inference. Point estimation, interval estimating, and testing hypotheses, Bayesian approaches to inference.
UC Irvine OpenCourseWare 0:22
Lecture 01. 1:44:39
Lecture 02. 1:34:01
Lecture 03. 1:37:19
Lecture 04. 1:39:28
Lecture 05. 1:41:11
Lecture 06. 1:31:32
Lecture 07. 1:29:05
Lecture 08. 1:15:21
Lecture 09. 1:40:59
Lecture 10. 1:41:36
Lecture 11. 1:32:37
Lecture 12. 1:32:02
Lecture 13. 1:38:45
Lecture 14. 1:39:25
Lecture 15. 1:37:54
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