Every now and then I want to generate normally distributed values in something like Perl, which does not have built-in functions for it. Unfortunately, there’s no easily remembered way to generate numbers from the normal distribution. I just learned the best way to do it: don’t. Generate logistically distributed values instead.
KONKRET GRANSKNING. En vanlig missuppfattning är att migrationspolitiken har varit för generös i landet, eller att migrationen har varit ”okontrollerad”. Som framgår av offentligt tillgänglig statistik så har bara en liten del av alla uppehållstillstånd gått till flyktingar och asylsökande
arXiv is a free distribution service and an open-access archive for 2,299,453 scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics.
open-access archive for 2,273,366 scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics.
This book will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it. In this book, you will find a practicum of skills for data science. Just as a chemist learns how to clean test tubes and stock a lab, you’ll learn how to clean data and draw plots—and many other things besides. These are the skills that allow data science to happen, and here you will find the best practices for doing each of these things with R. You’ll learn how to use the grammar of graphics, literate programming, and reproducible research to save time. You’ll also learn how to manage cognitive resources to facilitate discoveries when wrangling, visualising, and exploring data.
El Objetivo del paquete aprendeR es facilitar que nuevas personas puedan R moderno con una curva de aprendizaje baja, y evitando que el inglés sea una barrera para que se puedan centrar en el aprendizaje competencial de R. Se incluyen traducciones al castellano de tutoriales presentes en otros paquetes (learnr, tutorial.helpers, r4ds.tutorials, ...), y eventualmente nuevos tutoriales más adelante.
Natercia Valle tells a cautionary tale about the use of learning analytics dashboards to increase student motivation, and the challenges of translating theory into design solutions.
March 20, 2022
C. Lienhard, и T. Enßlin. (2018)cite arxiv:1807.02709Comment: 36 pages, 4 figures, available at https://gitlab.mpcdf.mpg.de/ift/HMCF, see also arXiv:1708.01073.
B. De Palma, M. Erba, L. Mantovani, и N. Mosco. (2017)cite arxiv:1703.02766Comment: New simulations, extended statistics, improved results and fits. 23 pages, 3 figures, 3 tables. Link of the program UNEW: http://bitbucket.org/betocollaboration/unew/.
Ž. Stojanac, D. Suess, и M. Kliesch. (2017)cite arxiv:1711.10516Comment: 17+10 pages, 30 figures. V2: Minor improvements of the presentation and incomplete funding information corrected.
M. Lindvall, и J. Molin. (2020)cite arxiv:2001.07455Comment: Accepted for presentation in poster format for the ACM CHI'19 Workshop <Emerging Perspectives in Human-Centered Machine Learning>.
U. Wolff. (2003)cite arxiv:hep-lat/0306017Comment: 22 pages, 4 figures, link-address for software download, V4: Improvement in eq.(58) and (42) for error of tau_int => new version of software.Only subleading error terms affected, results should remain compatible.
S. Romiti, и S. Simula. (2019)cite arxiv:1907.09926Comment: 45 pages, 9 figures, 13 tables; few references added and few minor points addressed; version to appear in PRD.
A. Joseph. (2019)cite arxiv:1912.10997Comment: 122 pages, 34 figures, several appendices. These lecture notes are based on the three lectures given at the 2019 Joburg School in Theoretical Physics: Aspects of Machine Learning, Mandelstam Institute for Theoretical Physics, The University of the Witwatersrand, Johannesburg, South Africa (November 11 - 15, 2019).