Fixed Effects and Random Effects
Brief overview in plain English of the differences between the types of effects. Problems with each model and how to overcome them.
From playlist Experimental Design
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
Prob & Stats - Random Variable & Prob Distribution (4 of 53) Types of Random Variable
Visit http://ilectureonline.com for more math and science lectures! In this video I will define 2 types of random variables (discrete and continuous variables). Next video in series: http://youtu.be/mtt3h54aSkk
From playlist iLecturesOnline: Probability & Stats 2: Random Variable & Probability Distribution
Intro to a Variable as a Changing Value or Placeholder
This video defines a variable and provides examples of a variable used as a changing value or a placeholder http://mathispower4u.com
From playlist Algebraic Structures Module
VARIABLES in Statistical Research (2-1)
A variable is any characteristic that can vary. An organized collection of numbers can be a variable. Qualitative variables indicate an attribute or belongingness to a category. Dichotomous variables are discrete variables that can have two and only two values. Quantitative variables indic
From playlist Forming Variables for Statistics & Statistical Software (WK 2 - QBA 237)
Statistics: Ch 5 Discrete Random Variable (2 of 27) What is a Discrete 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 discrete random variable can be a count of something, an integer, as how many times a coin comes up “heads” or “tails
From playlist STATISTICS CH 5 DISCRETE RANDOM VARIABLE
Generalized Linear Model (Part A)
Regression Analysis by Dr. Soumen Maity,Department of Mathematics,IIT Kharagpur.For more details on NPTEL visit http://nptel.ac.in
From playlist IIT Kharagpur: Regression Analysis | CosmoLearning.org Mathematics
Tamir Bendory - Recovering small molecular structures using cryo-EM - IPAM at UCLA
Recorded 16 November 2022. Tamir Bendory of Tel Aviv University Electrical Engineering presents "Recovering small molecular structures using cryo-EM" at IPAM's Cryo-Electron Microscopy and Beyond Workshop. Abstract: Any current cryo-EM algorithmic pipeline entails recovering the 3-D struct
From playlist 2022 Cryo-Electron Microscopy and Beyond
Lisa Nickerson - Addressing Confounds in Neuroimaging Machine Learning Predictions - IPAM at UCLA
Recorded 13 January 2023. Lisa Nickerson of Harvard Medical School presents "Addressing Confounds in Neuroimaging Machine Learning Predictions" at IPAM's Explainable AI for the Sciences: Towards Novel Insights Workshop. Learn more online at: http://www.ipam.ucla.edu/programs/workshops/expl
From playlist 2023 Explainable AI for the Sciences: Towards Novel Insights
Stefano Soatto: "Invariance and disentanglement in deep representations"
New Deep Learning Techniques 2018 "Invariance and disentanglement in deep representations" Stefano Soatto, University of California, Los Angeles (UCLA) Abstract: Theories of Deep Learning are like anatomical parts best not named explicitly in an abstract: Everyone seems to have one. That
From playlist New Deep Learning Techniques 2018
Random Variable Examples with Discrete and Continuous
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Random Variable Examples with Discrete and Continuous
From playlist Statistics
Likelihood | Log likelihood | Sufficiency | Multiple parameters
See all my videos here: http://www.zstatistics.com/ *************************************************************** 0:00 Introduction 2:17 Example 1 (Discrete distribution: develop your intuition!) 7:25 Likelihood 8:52 Likelihood ratio 10:00 Likelihood function 11:05 Log likelihood funct
From playlist Statistical Inference (7 videos)
Lec 13 | MIT 2.830J Control of Manufacturing Processes, S08
Lecture 13: Modeling testing and fractional factorial models Instructor: Duane Boning, David Hardt View the complete course at: http://ocw.mit.edu/2-830JS08 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 2.830J, Control of Manufacturing Processes S08
Experimental Design Module 3b: Block Design
This episode is part of Healthcare Triage’s series on Improving Reproducibility in Research. The Introduction to the series is here: https://www.youtube.com/watch?v=EvoVb_QLRK8 A blog post with more information on the series is here: http://theincidentaleconomist.com/wordpress/improving-re
From playlist Experimental Design
Learning Controllable Representations - Richard Zemel
Seminar on Theoretical Machine Learning Topic: Learning Controllable Representations Speaker: Richard Zemel Affiliation: University of Toronto; Member, School of Mathematics Date: April 2, 2020 For more video please visit http://video.ias.edu
From playlist Mathematics
Kyle Cranmer - Simulation-based Inference for Gravitational Wave Astronomy - IPAM at UCLA
Recorded 17 November 2021. Kyle Cranmer of New York University presents "Simulation-based Inference for Gravitational Wave Astronomy" at IPAM's Workshop III: Source inference and parameter estimation in Gravitational Wave Astronomy. Abstract: I will briefly review the taxonomy of simulatio
From playlist Workshop: Source inference and parameter estimation in Gravitational Wave Astronomy
The Poisson is a classic distribution used in operational risk. It often fits (describes) random variables over time intervals. For example, it might try to characterize the number of low severity, high frequency (HFLS) loss events over a month or a year. It is a discrete function that con
From playlist Statistics: Distributions
02 05 Part 3 of 3 Model Selection
From playlist Coursera Regression V2
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