A16 The method of variation of parameters
Starting the derivation for the equation that is used to find the particular solution of a set of differential equations by means of the variation of parameters.
From playlist A Second Course in Differential Equations
Calculus: Bisection, Secant, and Newton
This video provides a unique view into what Calculus is, what it can be used for, and how it can be used in the real world. To illustrate how these three concepts are all connected, I consider the two very important examples of finding the solution of a complicated equation and finding the
From playlist Calculus
(8.1) A General Approach to Nonlinear Differential Questions
This video briefly describes the approach to gaining information about the solution to nonlinear differential equations. https://mathispower4u.com
From playlist Differential Equations: Complete Set of Course Videos
C28 Variation of parameters Part 1
We have already seen variation of parameters in action, but here we expand the method for use in second-order linear DE's, even with non-constant coefficients.
From playlist Differential Equations
B01 An introduction to numerical methods
Most differential equations cannot be solved by the analytical techniques that we have learned up until now. I these cases, we can approximate a solution by a set of points, by using a variety of numerical methods. The first of these is Euler's method.
From playlist A Second Course in Differential Equations
Euler’s method - How to use it?
► My Differential Equations course: https://www.kristakingmath.com/differential-equations-course Euler’s method is a numerical method that you can use to approximate the solution to an initial value problem with a differential equation that can’t be solved using a more traditional method,
From playlist Differential Equations
Melanie Zeilinger: "Learning-based Model Predictive Control - Towards Safe Learning in Control"
Intersections between Control, Learning and Optimization 2020 "Learning-based Model Predictive Control - Towards Safe Learning in Control" Melanie Zeilinger - ETH Zurich & University of Freiburg Abstract: The question of safety when integrating learning techniques in control systems has
From playlist Intersections between Control, Learning and Optimization 2020
Data Mining with Weka (4.3: Classification by regression)
Data Mining with Weka: online course from the University of Waikato Class 4 - Lesson 3: Classification by regression https://weka.waikato.ac.nz/ Slides (PDF): https://www.cs.waikato.ac.nz/ml/weka/mooc/dataminingwithweka/ https://twitter.com/WekaMOOC https://wekamooc.blogspot.co.nz/ De
From playlist Data Mining with Weka
Setting Variables with Levels of Measurement: Discover Statistics with JASP for Beginners (3 of 6)
Each variable in JASP is assigned a level of measurement (nominal, nominal text, ordinal, or scale). We learn how to change or set those levels and how to set and adjust value levels for categorical variables. I cover whether we have to set levels and how setting levels benefits us. This i
From playlist Discovering Statistics with JASP
28th Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series Talk
Date: Wednesday, June 16, 2021, 10:00am Eastern Time Zone (US & Canada) Speaker: Yiqui Dong Title: Model Error Matters – CT reconstruction with uncertain view angles Abstract: Inverse problems are mathematical problems that arise when one wants to recover “hidden” information from indir
From playlist Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series
JUDGMENT and SNOWBALL Non-random Sampling (12-6)
Judgment sampling (a.k.a., expert sampling, authoritative sampling, purposive sampling, judgmental sampling) is a technique in which the sample is selected based on the researcher’s (or other experts’) existing knowledge or professional judgment. It may provide highly accurate findings wit
From playlist Sampling Distributions in Statistics (WK 12 - QBA 237)
TDLS - Classics: SMOTE, Synthetic Minority Over-sampling Technique (algorithm)
Toronto Deep Learning Series, 26 November 2018 Paper: https://arxiv.org/pdf/1106.1813.pdf Speaker: Jason Grunhut (Telus Digital) Host: Telus Digital Date: Nov 26th, 2018 SMOTE: Synthetic Minority Over-sampling Technique An approach to the construction of classifiers from imbalanced da
From playlist Math and Foundations
Latent class cluster analysis with free software Jamovi
In this video, I will show how to do a latent class cluster analysis with free software Jamovi. Please download Jamovi from this link: https://www.jamovi.org/download.html Recommended papers: 1. Latent class cluster analysis paper: https://journals.sagepub.com/doi/abs/10.1177/0276236619
From playlist Jamovi software
Excel Statistical Analysis 01: Data & Statistics
Download Excel File: https://excelisfun.net/files/Ch01-ESA.xlsm Topics in video: (00:00) Introduction (00:54) Use File Explorer, Show File Extensions, Create Folder for class (02:59) Use People Web Site to download files for this class (05:58) How to open Excel files using File Explorer (0
From playlist Excel Statistical Analysis for Business Class Playlist of Videos from excelisfun
A17 Deriving the equation for the particular solution
Finishing the derivation for the equation that is used to find the particular solution of a set of differential equations by means of the variation of parameters.
From playlist A Second Course in Differential Equations
Differential Equation in terms of Dependent Variable (1 of 2: Partial Fractions)
More resources available at www.misterwootube.com
From playlist Applications of Calculus
Lec 24 | MIT 6.451 Principles of Digital Communication II
Linear Gaussian Channels View the complete course: http://ocw.mit.edu/6-451S05 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.451 Principles of Digital Communication II