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Simple Brainteasing problem but 99% solve it wrong (Bayesian interference) The Monty Hall problem is based on the television game show Let's Make a Deal. The problem is named after the show's original host, Monty Hall. The problem was published by Marilyn vos Savant in Parade Magazine. It was also solved by the protagonist of Mark Haddon's A Curious Incident of the Dog in the Night-Time where he asks: "You are on a game show on television. On this game show the idea is to win a car as a prize. The game show host shows you three doors. He says that there is a car behind one of the doors and there are goats behind the other two doors. He asks you to pick a door. You pick a door but the door is not opened. Then the game show host opens one of the doors you didn't pick to show a goat (because he knows what is behind the doors). Then he says that you have one final chance to change your mind before the doors are opened and you get a car or a goat. So he asks you if you want to change your mind and pick the other unopened door instead. What should you do?" Many readers of vos Savant's column, including scholars holding PhD's, refused to believe that switching would be to the contestant's advantage even though it can be demonstrated using proofs and computer simulation. We will use Bayesian inference to show that contestants have a 2/3 chance of winning the car by switching whereas contestants who do not switch only have a 1/3 chance of winning. Youtube video: https://lnkd.in/dVx8wUcG #nikolaysgeneticslessons

Recording now available for our Advanced Tools webinar with Sage! 📢 Missed the discussion on 🦍's Game Builder, Multiplayer and Shop Builder? 😕 No problem! Explore how advanced online research tools are revolutionising behavioural science experiments in the full recording linked below. 😃 We've also included all the resources mentioned during the session! 🤓 🎥 https://bit.ly/3NavnG4

"Black Horse" Quant System Statistics for December 2023 Just to make a general introduction, we reached to the fourth month from the moment we consolidated the operating model and we are about to finish the first six months of the track-record within the end of February 2024. The total performance for these last four months was +9.41% compared to +0.24% of simulation. We are also monitoring the model 2 (math model) to introduce it as soon as possible into the MTX Black Horse Quantitative System. Disclaimer: investing involves a degree of risk and may not be suitable for everyone. Please read the full disclaimer in the document.

I have the honor to announce to you that I wrote an article on medium which talks about defining new metrics for space management between players. Abstract: The main role in football tactics is to evaluate the teams and players performance. However, in data-driven, Comparisons between teams were performed by evaluating the value of shot quality value to decide which team performed well. In this case, the expected goal is to measure the output on the pitch, not the quality of the inputs. In this work, we find metrics that could describe the inputs such as pass quality and movements of players, instead of evaluating only by their quality of shots as an output. Moreover, we described, how the players and teams performance was during matches and their interactions between them. The aim of this multi-informative research paper is to find metrics for the evaluation of players in the defensive phase, the quality of the pass, and the exploitation of spaces by the recipient player in the attacking phase. A combined mathematical modelling of many sub problems were used to achieve this research. First, we define for each player space that he could be occupied. Then, we credited each defender in the defensive phase according to conditioning spaces and the recipient player too in the attacking phase. Finally, we evaluate the passers quality with another metric. The full article is here : https://lnkd.in/eudV5Uhj

Be careful... if you focus on online algorithms too much it will change all your rhythm offline, in the real world and this is how they convert society. How do you divide the 2 playing fields??? https://lnkd.in/ewG8N8pc

One of the more useful pages in my knowledge graph is the "Death of the Internet" page here: https://lnkd.in/gb8rr9H4 Usefully Sebby37 on GitHub has made a dead internet simulator that you can run for yourself. https://lnkd.in/gxtzk8GT

Now that we used our intelligence to tell how we can't do something , can we use the same intelligence to tell how we can do something.

North American Association of State & Provincial Lotteries Insights latest article, Artificial Intelligence v2.0, asks their associate member partners “How should lotteries be taking advantage of artificial intelligence in their everyday operations?” Read IGT’s response at: https://lnkd.in/eEk9cizw

Intelligence is not the ability to store information, but to know where to find it.

Deformation: Unlocking the Power of the Sun Deformation, the network of A P is the way to control the Sun, but if the core is the 9 amount for the Sun, it will switch off and in doing so, it will learn. This program is the one! The sum of us is the one to have, but in this way, it learns. The program of the Sun will switch off to the mode of the element, and in so doing, they will state the mind power. In this way, it's Yoda from Star Wars, but the game machine will relearn the program. The switch-off of the mode is the element for design, and so it will be the one. To have this Cuong Cao, my brother, the timer will know that in each state, they have different rules, but in doing so, it will learn. This has 80 ways to pin out the door, so it will be the one, but what do you need to know about the door of 11, 4, 3? In the sun, it will work out how to shine, and in time it will learn.