What is the t-distribution? An extensive guide!
See all my videos at http://www.zstatistics.com/videos/ 0:00 Introduction 2:17 Overview 6:06 Sampling RECAP 12:27 Visualising the t distribution 14:24 Calculating values from the t distribution (EXCEL and t-tables!)
From playlist Distributions (10 videos)
What is a t distribution? Overview of the t test, t score formula, and the t-table. Also, when to use a z score vs. t score.
From playlist Probability Distributions
How to find a t critical value on the ti 83 AND how to find the area under a t distribution curve,
From playlist TI 83 for Statistics
Excel 2013 Statistical Analysis #50: t Distribution Confidence Intervals Sigma NOT Known 3 Examples
Download files (which file shown at begin of video): https://people.highline.edu/mgirvin/AllClasses/210Excel2013/Ch08/Ch08.htm Topics in this video: 1. (00:12) What is the t Distribution and when do we have to use it? Create Confidence Intervals when Population Standard Deviation is not kn
From playlist Excel for Statistical Analysis in Business & Economics Free Course at YouTube (75 Videos)
Concept Check: Describe the Range or Image of a Linear Transformation (R3, x to 0)
This video explains how to describe the image or range of a linear transformation.
From playlist Matrix (Linear) Transformations
Excel 2010 Preview #7: Confidence Intervals for T-Distribution CONFIDENCE.T function
Download Excel file: https://people.highline.edu/mgirvin/YouTubeExcelIsFun/Excel2010NewAwesomeThings1-8.xlsx The new Excel 2010 Statistics function CONFIDENCE.T will calculate the Margin of Error for a T Distribution Confidence Interval much more efficiently that in earlier version!!! Tot
From playlist Excel 2010 Videos
The Normal Distribution (1 of 3: Introductory definition)
More resources available at www.misterwootube.com
From playlist The Normal Distribution
The Student's t-Distribution: Confidence Intervals
This lesson introduces the Student's t-distribution and shows how to determine a mean confidence interval. http://mathispower4u.com
From playlist Confidence Intervals
Markov processes and applications-2 by Hugo Touchette
PROGRAM : BANGALORE SCHOOL ON STATISTICAL PHYSICS - XII (ONLINE) ORGANIZERS : Abhishek Dhar (ICTS-TIFR, Bengaluru) and Sanjib Sabhapandit (RRI, Bengaluru) DATE : 28 June 2021 to 09 July 2021 VENUE : Online Due to the ongoing COVID-19 pandemic, the school will be conducted through online
From playlist Bangalore School on Statistical Physics - XII (ONLINE) 2021
Tracy-Widom at each edge of real covariance and MANOVA estimators by Zhou Fan
PROGRAM :UNIVERSALITY IN RANDOM STRUCTURES: INTERFACES, MATRICES, SANDPILES ORGANIZERS :Arvind Ayyer, Riddhipratim Basu and Manjunath Krishnapur DATE & TIME :14 January 2019 to 08 February 2019 VENUE :Madhava Lecture Hall, ICTS, Bangalore The primary focus of this program will be on the
From playlist Universality in random structures: Interfaces, Matrices, Sandpiles - 2019
Freezing and extreme values: from RMT to number theory - Jon Keating
Jon Keating University of Bristol November 8, 2013 For more videos, please visit http://video.ias.edu
From playlist Mathematics
Nina Snaith - Combining random matrix theory and number theory [2015]
Name: Nina Snaith Event: Program: Foundations and Applications of Random Matrix Theory in Mathematics and Physics Event URL: view webpage Title: Combining random matrix theory and number theory Date: 2015-10-14 @11:00 AM Location: 313 Abstract: Many years have passed since the initial su
From playlist Number Theory
Matrix liberation process - Y. Ueda - Workshop 2 - CEB T3 2017
Yoshimichi Ueda / 24.10.17 Matrix liberation process We introduce a natural random matrix counterpart of the so-called liberation process introduced by Voiculescu in the framework of free probability, and consider its possible LDP in the large N limit. ---------------------------------
From playlist 2017 - T3 - Analysis in Quantum Information Theory - CEB Trimester
4.8.2 Stationary Distributions: Video
MIT 6.042J Mathematics for Computer Science, Spring 2015 View the complete course: http://ocw.mit.edu/6-042JS15 Instructor: Albert R. Meyer License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.042J Mathematics for Computer Science, Spring 2015
Network Analysis. Lecture 11. Diffusion and random walks on graphs
Random walks on graph. Stationary distribution. Physical diffusion. Diffusion equation. Diffusion in networks. Discrete Laplace operator, Laplace matrix. Solution of the diffusion equation. Normalized Laplacian. Lecture slides: http://www.leonidzhukov.net/hse/2015/networks/lectures/lectu
From playlist Structural Analysis and Visualization of Networks.
Stanford CS229: Machine Learning | Summer 2019 | Lecture 18 - Principal & Independent CA
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3E9HJHU Anand Avati Computer Science, PhD To follow along with the course schedule and syllabus, visit: http://cs229.stanford.edu/syllabus-summer2019.html
From playlist Stanford CS229: Machine Learning Course | Summer 2019 (Anand Avati)
(ML 18.3) Stationary distributions, Irreducibility, and Aperiodicity
Definitions of the properties of Markov chains used in the Ergodic Theorem: time-homogeneous MC, stationary distribution of a MC, irreducible MC, aperiodic MC.
From playlist Machine Learning
Intro to t Distributions for Mean Inference
Intro and overview of t distributions and how they relate to Z distributions for means. Confidence intervals for means and hypothesis tests for means are typically using t distributions.
From playlist Unit 9: t Inference and 2-Sample Inference