In mathematics and logic, plural quantification is the theory that an individual variable x may take on plural, as well as singular, values. As well as substituting individual objects such as Alice, the number 1, the tallest building in London etc. for x, we may substitute both Alice and Bob, or all the numbers between 0 and 10, or all the buildings in London over 20 stories. The point of the theory is to give first-order logic the power of set theory, but without any "existential commitment" to such objects as sets. The classic expositions are Boolos 1984 and Lewis 1991. (Wikipedia).
Quantized Energy Equation (Quantum Physics)
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From playlist Quantum Mechanics
Percentiles, Deciles, Quartiles
Understanding percentiles, quartiles, and deciles through definitions and examples
From playlist Unit 1: Descriptive Statistics
(PP 6.1) Multivariate Gaussian - definition
Introduction to the multivariate Gaussian (or multivariate Normal) distribution.
From playlist Probability Theory
Statistics 5_1 Confidence Intervals
In this lecture explain the meaning of a confidence interval and look at the equation to calculate it.
From playlist Medical Statistics
More Standard Deviation and Variance
Further explanations and examples of standard deviation and variance
From playlist Unit 1: Descriptive Statistics
Derivations.2.Derivation of Variance
This video is brought to you by the Quantitative Analysis Institute at Wellesley College. The material is best viewed as part of the online resources that organize the content and include questions for checking understanding: https://www.wellesley.edu/qai/onlineresources
From playlist Optional - Derivations
More Standard Deviation and Variance of Joint Discrete Random Variables
Further example and understanding of Joint Discrete random variables and their standard deviation and variance
From playlist Unit 6 Probability B: Random Variables & Binomial Probability & Counting Techniques
DDPS | Deep learning for reduced order modeling
Description: Reduced order modeling (ROM) techniques, such as the reduced basis method, provide nowadays an essential toolbox for the efficient approximation of parametrized differential problems, whenever they must be solved either in real-time, or in several different scenarios. These ta
From playlist Data-driven Physical Simulations (DDPS) Seminar Series
(PP 6.6) Geometric intuition for the multivariate Gaussian (part 1)
How to visualize the effect of the eigenvalues (scaling), eigenvectors (rotation), and mean vector (shift) on the density of a multivariate Gaussian.
From playlist Probability Theory
UCF Center for Ethics: "Quantification in Ethics"
"Quantification in Ethics," presented by Dr. James Franklin, former Professor in the School of Mathematics and Statistics at the University of New South Wales, on November 30, 2021. Ethics is usually thought of as involving no quantification – it is about discussing principles and resolvi
From playlist Research by our staff
EMinar 3,4: Michael Pyrcz - Machine Learning-based Geoscience
The subsurface resource industry has a long history of working with large, complicated geoscience and engineering datasets. The subsurface industry been working with ‘big data’ for decades! There is a growing toolbox of legacy and new emerging data-driven methods available that may offer i
From playlist Random Talks
Find this video and other talks given by worldwide mathematicians on CIRM's Audiovisual Mathematics Library: http://library.cirm-math.fr. And discover all its functionalities: - Chapter markers and keywords to watch the parts of your choice in the video - Videos enriched with abstracts, b
From playlist Mathematical Aspects of Computer Science
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)
(PP 6.4) Density for a multivariate Gaussian - definition and intuition
The density of a (multivariate) non-degenerate Gaussian. Suggestions for how to remember the formula. Mathematical intuition for how to think about the formula.
From playlist Probability Theory