@semuhi @CA_Penel @KellgrenLeila@johnchinphd@Fjelde@esdebruin Hi @semuhi nice to meet you. It depends on the team/company size and project complexity. For most of the work 1. GitHub (version control) 2. Slack (chat) 3. Trello (kanban board) 4. Google docs (docs & decks). I love Notion but I use it as a personal tool.
@seanjtaylor@hspter It’s just a rule of thumb. In Ch.3 of Statistical Methods for Research Workers (1925) Fisher discusses normal tables and says it is “convenient” to use 1.96 “as a limit in judging whether a deviation is to be considered significant or not”.
The first article from the Peacekeeping Operations Corpus is now available on @JPR_journal 🎉🎉🎉
Thanks to everyone who engaged with this idea and contributed to the project.
Repo: https://t.co/spmkKemOEj
Data: https://t.co/P7y8jx0kcl
Article: https://t.co/orcTfhyKD8
@ElioAmicarelli & @jessdisal answer this question by developing the Peacekeeping Operations Corpus (PKOC) dataset which is a machine-readable collection of the UN Secretary-General’s Reports on PKOs, covering the period between 1994 to 2020.
@PhDemetri Hi Demetri, I'm surprised. I have the feeling that given the initial statement, a logical proposition to follow would be that hypothesis testing is more useful than stupid🤔
@CrypTomer_pers@ProbFact Hi! Yes and no...Philosophers have speculated about probability during ancient history. However, modern probability theory started in the 17th century.
Many open problems in #AI and #ML are related to causality. ML pipelines may produce highly predictive models that fall short in deployment. The reason? A usual suspect from the causal inference literature: model underspecification! https://t.co/VFEJaFdMwK
#RStats#DataScience
The article "Forecasting: theory and practice" provides an extensive review of the field: https://t.co/QKqAYb9QPf
I liked the encyclopedic approach a lot so I extracted a full TOC to quickly eyeball all its subsections: https://t.co/7oBnMUI3kd
#DataScience#rstats#forecasting
Our article, "Forecasting: theory and practice", is the first encyclopedic-type approach to the field of forecasting, covering many different methods and applications.
My huge thanks to my many co-authors for making this possible.
Download here: https://t.co/nkbgo7pALR
@fotpetr I really like the encyclopedic approach of this extensive review! I thought it would be useful to have a full TOC to quickly eyeball all subsections so I took the liberty of extracting one: https://t.co/p9LD9ZOv8j