Scale parameter
In probability theory and statistics, a scale parameter is a special kind of numerical parameter of a parametric family of probability distributions. The larger the scale parameter, the more spread out the distribution. (Wikipedia).
In probability theory and statistics, a scale parameter is a special kind of numerical parameter of a parametric family of probability distributions. The larger the scale parameter, the more spread out the distribution. (Wikipedia).
This video shows how to use scale to determine the dimensions of a proportional model. http://mathispower4u.yolasite.com/
From playlist Unit Scale and Scale Factor
Definition of scale variable for SPSS, psychology/behavioral science & finance.
From playlist Types of Variables
This video shows how to use unit scale to determine the actual dimensions of a model and how to determine the dimensions of a model from an actual dimensions. http://mathispower4u.yolasite.com/
From playlist Unit Scale and Scale Factor
Percentiles, Deciles, Quartiles
Understanding percentiles, quartiles, and deciles through definitions and examples
From playlist Unit 1: Descriptive Statistics
More Standard Deviation and Variance
Further explanations and examples of standard deviation and variance
From playlist Unit 1: Descriptive Statistics
Populations, Samples, Parameters, and Statistics
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Populations, Samples, Parameters, and Statistics
From playlist Statistics
Scale Factor, Similar Triangles, and Proportions
This video defines scale factor and then uses proportions and equivalent ratios to determine missing values is similar shapes. http://mathispower4u.com
From playlist Number Sense - Decimals, Percents, and Ratios
21 Spatial Data Analytics: Spatial Scale
Subsurface modeling course lecture on scale.
From playlist Spatial Data Analytics and Modeling
Scales of Measurement - Nominal, Ordinal, Interval, & Ratio Scale Data
This statistics video tutorial provides a basic introduction into the different forms of scales of measurement such as nominal, ordinal, interval, and ratio scale data. My Website: https://www.video-tutor.net Patreon Donations: https://www.patreon.com/MathScienceTutor Amazon Store: htt
From playlist Statistics
From playlist COMP0168 (2020/21)
Ian McCulloch: "Finite-entanglement scaling functions at quantum critical points"
Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021 Workshop II: Tensor Network States and Applications "Finite-entanglement scaling functions at quantum critical points" Ian McCulloch - University of Queensland Abstract: For translationally invariant infinite
From playlist Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021
Kaggle Reading Group: EfficientNet (Part 2) | Kaggle
This week we'll be starting EfficientNet (Tan & Le, 2019), which was published at ICML 2019. The paper proposes a new family of models that are both smaller and faster to train than traditional convolutional neural networks. Link to paper: http://proceedings.mlr.press/v97/tan19a/tan19a.pd
From playlist Kaggle Reading Group | Kaggle
Robert Batterman - Mesoscale Models and Many-Body Systems - IPAM at UCLA
Recorded 17 February 2022. Robert Batterman of the University of Pittsburgh presents "Mesoscale Models and Many-Body Systems" at IPAM's Mathematics of Collective Intelligence Workshop. Abstract: Many-body systems often display different behaviors at different scales. The behavior of a flui
From playlist Workshop: Mathematics of Collective Intelligence - Feb. 15 - 19, 2022.
Galaxy bias and its implications for forward models (...) - F. Schmidt - Workshop 1 - CEB T3 2018
Fabian Schmidt (MPA) / 21.09.2018 Galaxy bias and its implications for forward models of the large-scale structure ---------------------------------- Vous pouvez nous rejoindre sur les réseaux sociaux pour suivre nos actualités. Facebook : https://www.facebook.com/InstitutHenriPoincare/
From playlist 2018 - T3 - Analytics, Inference, and Computation in Cosmology
Critical dynamics (Lecture - 01) by Uwe C Täuber
Bangalore School on Statistical Physics - VIII DATE: 28 June 2017 to 14 July 2017 VENUE: Ramanujan Lecture Hall, ICTS, Bengaluru This advanced level school is the eighth in the series. This is a pedagogical school, aimed at bridging the gap between masters-level courses and topics in s
From playlist Bangalore School on Statistical Physics - VIII
New Approaches to the Hierarchy Problem I - Nathaniel Craig
Prospects in Theoretical Physics Particle Physics at the LHC and Beyond Topic: New Approaches to the Hierarchy Problem II Speaker: Nathaniel Craig Date: July 18, 2017
From playlist PiTP 2017
SUSY models: theory/pheno by Howie Baer
Discussion Meeting : Hunting SUSY @ HL-LHC (ONLINE) ORGANIZERS : Satyaki Bhattacharya (SINP, India), Rohini Godbole (IISc, India), Kajari Majumdar (TIFR, India), Prolay Mal (NISER-Bhubaneswar, India), Seema Sharma (IISER-Pune, India), Ritesh K. Singh (IISER-Kolkata, India) and Sanjay Kuma
From playlist HUNTING SUSY @ HL-LHC (ONLINE) 2021
Critical dynamics (Lecture - 02) by Uwe C Täuber
Bangalore School on Statistical Physics - VIII DATE: 28 June 2017 to 14 July 2017 VENUE: Ramanujan Lecture Hall, ICTS, Bengaluru This advanced level school is the eighth in the series. This is a pedagogical school, aimed at bridging the gap between masters-level courses and topics in s
From playlist Bangalore School on Statistical Physics - VIII
Henry Adams (10/11/17): Metric reconstruction via optimal transport
Given a sample of points X in a metric space M and a scale parameter r, the Vietoris-Rips simplicial complex VR(X;r) is a standard construction to attempt to recover M from X up to homotopy type. A deficiency of this approach is that VR(X;r) is not metrizable if it is not locally finite, a
From playlist AATRN 2017
The Meaning of Numbers – Continuous (Scale) Data (1-3)
Numbers can do many functions. Some numbers stand in for names or create categories (nominal & ordinal). Other numbers quantify amounts and measurements (interval & ratio). We continue our exploration of numbers with scale data: interval and ratio. You will learn the subtle distinctions be
From playlist WK1 Numbers and Variables - Online Statistics for the Flipped Classroom