All,
Maggie Lieu is our YouTube manager and she has written a draft script for a video that will welcome people to the channel. This is not technical, not a mission statement and it is meant to be 3-5 min long.
Maggie will be presenting it: here is her channel on Astro Physics to get an idea of where she is coming from.
The script is below, some ground rules please:
- Please be kind in your comments. It is possible to really not like something, communicate that, and leave all parties happy.
- Concrete edits are more useful than general observations.
- Feel free to rewrite as you see fit. But understand that it may not be adopted.
- You have until the end of the Thursday meeting at around 12:30 EDT to comment.
Here is a copy of the draft:
Have you ever wanted to predict the stock market or perhaps just the outcome of a football match? Are you trying to take your scientific analysis to the next level or maybe prepare for the next global disaster? It seems like you need statistical inference⌠but statistics is hard and youâre lazyâŚ
Well youâre in luck! Hello and welcome to the official Stan Youtube channel! Stan is probabilistic programming language that is designed to make it easier for you to do statistical inference. Using Stan you can do quick proto-typing of complex models in just a few lines of code.
Stan is a variation of Hamiltonian Monte Carlo called the No-U-Turn sampler or NUTS for short. We will come back to just what that means in a future video, but in short, it allows for fast exploration of the posterior probability distribution and is highly scalable! Think MILLIONS of parameters!
Stan has been employed in a wide spectrum of fields including: social science to analyse political behavior and election results, in pharmacology to study the dosages of drug administration, in market research to understand the market trends of chocolate bars, in medical imaging to detect tumours, and even in astronomy to constrain dark matter and dark energy!
Stan runs with a command line executable, but it can also be accessed via popular interfaces of R, Python, MATLAB, Mathematica, Julia and Stata, and runs on all major platforms (linux, mac, windows).
Most importantly, Stan is open source. This means you get a reliable and transparent code, that comes with a growing and supportive community. Our non-profit is able to provide free, high quality service thanks to the generous donations from our users. Find out how you can support Stan by checking out the link in the comment section below.
More information about Stan can be found on our website: mc-stan.org. Here we will be releasing new videos regularly covering everything from tips and techniques in Stan, to tutorials in Bayesian Statistics, and applications of Stan in a variety of case studies. Also donât forget to hit the subscribe button and click the bell, to make sure that youâll be the first to know when new content arrives! Thanks for watching and see you soon!