A numeric sequence is said to be statistically random when it contains no recognizable patterns or regularities; sequences such as the results of an ideal dice roll or the digits of π exhibit statistical randomness. Statistical randomness does not necessarily imply "true" randomness, i.e., objective unpredictability. Pseudorandomness is sufficient for many uses, such as statistics, hence the name statistical randomness. Global randomness and local randomness are different. Most philosophical conceptions of randomness are global—because they are based on the idea that "in the long run" a sequence looks truly random, even if certain sub-sequences would not look random. In a "truly" random sequence of numbers of sufficient length, for example, it is probable there would be long sequences of nothing but repeating numbers, though on the whole the sequence might be random. Local randomness refers to the idea that there can be minimum sequence lengths in which random distributions are approximated. Long stretches of the same numbers, even those generated by "truly" random processes, would diminish the "local randomness" of a sample (it might only be locally random for sequences of 10,000 numbers; taking sequences of less than 1,000 might not appear random at all, for example). A sequence exhibiting a pattern is not thereby proved not statistically random. According to principles of Ramsey theory, sufficiently large objects must necessarily contain a given substructure ("complete disorder is impossible"). Legislation concerning gambling imposes certain standards of statistical randomness to slot machines. (Wikipedia).
The Most Powerful Tool Based Entirely On Randomness
We see the effects of randomness all around us on a day to day basis. In this video we’ll be discussing a couple of different techniques that scientists use to understand randomness, as well as how we can harness its power. Basically, we'll study the mathematics of randomness. The branch
From playlist Classical Physics by Parth G
Scientific vs. STATISTICAL Experiments: Getting an Outcome (9-1)
In a science experiment, we measure stuff; in a statistical experiment, we compute probability. Scientific experiments yield replicable outcomes; statistical experiments yield random outcomes. Random means that we cannot reliably predict the outcome. A Random Variable is any outcome of a
From playlist Discrete Probability Distributions in Statistics (WK 9 - QBA 237)
Conceptual Questions about Random Variables and Probability Distributions
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Conceptual Questions about Random Variables and Probability Distributions
From playlist Statistics
(PP 3.1) Random Variables - Definition and CDF
(0:00) Intuitive examples. (1:25) Definition of a random variable. (6:10) CDF of a random variable. (8:28) Distribution of a random variable. A playlist of the Probability Primer series is available here: http://www.youtube.com/view_play_list?p=17567A1A3F5DB5E4
From playlist Probability Theory
Statistics: Ch 5 Discrete Random Variable (1 of 27) What is a Random Variable?
Visit http://ilectureonline.com for more math and science lectures! To donate: http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 We will learn a random variable is a variable which represents the outcome of a trial, an experiment, or an event. It is a specific n
From playlist STATISTICS CH 5 DISCRETE RANDOM VARIABLE
This lesson introduces the different sample methods when conducting a poll or survey. Site: http://mathispower4u.com
From playlist Introduction to Statistics
Prob & Stats - Random Variable & Prob Distribution (1 of 53) Random Variable
Visit http://ilectureonline.com for more math and science lectures! In this video I will define and gives an example of what is a random variable. Next video in series: http://youtu.be/aEB07VIIfKs
From playlist iLecturesOnline: Probability & Stats 2: Random Variable & Probability Distribution
Introduction to Random Variables
Introduction to random variables and probability distribution functions. More free lessons at: http://www.khanacademy.org/video?v=IYdiKeQ9xEI
From playlist Statistics
Discrete Math - 7.2.2 Random Variables and the Binomial Distribution
Introduction to random variables and finding probability of an event or cumulative probability using the binomial distribution. Textbook: Rosen, Discrete Mathematics and Its Applications, 7e Playlist: https://www.youtube.com/playlist?list=PLl-gb0E4MII28GykmtuBXNUNoej-vY5Rz
From playlist Discrete Math I (Entire Course)
10 Data Analytics: Spatiotemporal Stationarity
Lecture on random variables, random functions and the decision of stationarity. Now we are getting spatial!
From playlist Data Analytics and Geostatistics
*NOTE: This video was recorded in Fall 2017. The rest of the lectures were recorded in Fall 2016, but video of Lecture 1 was not available. MIT 18.650 Statistics for Applications, Fall 2016 View the complete course: https://ocw.mit.edu/18-650F16 Instructor: Philippe Rigollet In this lec
From playlist MIT 18.650 Statistics for Applications, Fall 2016
Lecture 11 - Statistical Significance
This is Lecture 11 of the CSE519 (Data Science) course taught by Professor Steven Skiena [http://www.cs.stonybrook.edu/~skiena/] at Stony Brook University in 2016. The lecture slides are available at: http://www.cs.stonybrook.edu/~skiena/519 More information may be found here: http://www
From playlist CSE519 - Data Science Fall 2016
Cryptography and Network Security by Prof. D. Mukhopadhyay, Department of Computer Science and Engineering, IIT Kharagpur. For more details on NPTEL visit http://nptel.iitm.ac.in
From playlist Computer - Cryptography and Network Security
Statistics Lesson #1: Sampling
This video is for my College Algebra and Statistics students (and anyone else who may find it helpful). It includes defining and looking at examples of five sampling methods: simple random sampling, convenience sampling, systematic sampling, stratified sampling, cluster sampling. We also l
From playlist Statistics
Giles Hooker - Ensembles of Trees and CLT's: Inference and Machine Learning
Professor Giles Hooker (Australian National University) presents "Ensembles of Trees and CLT's: Inference and Machine Learning", 14 May 2020. This seminar was organised by the Australian National University.
From playlist Statistics Across Campuses
PubHlth 194: Clinc Trans Rsrch-A. Lec 8: Biostatistics, Epidemiology and Research Design (BERD)
UCI PubHlth 194: Clinical and Translational Research Preparatory I (Fall 2012) Lec 08. Clinical and Translational Research Preparatory I -- Biostatistics, Epidemiology and Research Design (BERD) -- View the complete course: http://ocw.uci.edu/courses/pubhlth_194a_clinical_and_translational
From playlist PubHlth 194: Clinical & Translational Research Preparatory-A
Statistical significance on bus speeds | Probability and Statistics | Khan Academy
Courses on Khan Academy are always 100% free. Start practicing—and saving your progress—now: https://www.khanacademy.org/math/statistics-probability/significance-tests-confidence-intervals-two-samples/comparing-two-means/v/statistical-significance-on-bus-speeds Probability and statistics
From playlist Statistical studies | Probability and Statistics | Khan Academy
Ses 2 | MIT Abdul Latif Jameel Poverty Action Lab Executive Training
Session 2: Why randomize? Speaker: Dan Levy See the complete course at: http://ocw.mit.edu/jpal License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT Abdul Latif Jameel Poverty Action Lab Executive Training
(PP 6.1) Multivariate Gaussian - definition
Introduction to the multivariate Gaussian (or multivariate Normal) distribution.
From playlist Probability Theory
Branching Random Walks: Two Conjectures and a Theorem by Parthanil Roy
Vigyan Adda Talk Page (copy & paste the following link in the web browser):- www.icts.res.in/outreach/vigyan-adda/2022june Branching Random Walks: Two Conjectures and a Theorem (online) Speaker: Parthanil Roy (ISI - Bengaluru) When:4:30 pm to 6:00 pm Sunday, 05 June 2022 Where: Livest
From playlist Vigyan Adda