probability

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Towards Data Science
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Below is an open problem, an approachable problem, one perhaps you will be the one to solve! We send a bit over a noisy grid, starting from the origin and propagating out as a wave. Can we recover the original bit when looking at just the wavefront? This is easy to solve for 1D, mostly solved in 2D, and still open in 3D and above. Here is the lecture that introduced the problem to me, as well as …

mathematicsoptimizationprobability
nLab

There are a number of approaches to apply category theory to probability and related fields, such as statistics, information theory and dynamical systems. On one hand, one can study the existing structures in traditional probability theory (such as probability spaces, integration, and so on) using a categorical lens. For instance, the Giry monad models the formation of spaces of probability measu…

category-theorymathematicsprobability
nLab
Urs Schreiber
8d ago

A stochastic process describes a dynamical system evolving over a linearly ordered set (“time”), typically taken to be the (positive) integers or real numbers, whose dynamical laws of motion are morphisms in the Kleisli category of the Giry monad (or any other probability monad). By working in the larger category of algebras of that monad, a characterization of a stochastic processes can be model…

mathematicsprobabilitystochastic-calculus
Probably Overthinking It
AllenDowney
10d ago

Here’s a probability puzzle from a TED-Ed video called Can you solve the frog riddle? by Derek Abbott. It came up recently in this Reddit thread: You’re stranded in a rainforest after accidentally eating a poisonous mushroom. To survive the poison, you need to lick a certain species of frog. Only female frogs produce the antidote. Male and female frogs occur in equal numbers and look identical, b…

mathematicsprobability
Physics Forums
WMDhamnekar
10d ago

Two players start 1 meter away from a target. They simultaneously begin moving towards the target at a same constant speed. If the left player shoots when he is X meters from the target, his shot hit with a probability 1-X... Read more

mathematicsprobability
Hot Questions - Stack Exchange
Hot Questions - Stack Exchange
Nature
Science News
PhilPapers: Recent additions to PhilArchive

Horsten and Brickhill (2024) propose two methods for constructing non-Archimedean probability functions on the set-theoretic universe V: the finite snapshot approach and the bootstrapping approach. The mathematical execution is competent and the results within their framework are correct. This note raises three foundational concerns that the paper does not adequately address. First, the proposed …

mathematicsprobabilityset-theory
DEV Community

In This Article The Question The Intuition Trap: The Base Rate Fallacy The Mathematical Proof Python Simulation: 1,000,000 Trials Litigation Application: When Juries Get the Math Wrong The Question A cab was involved in a hit-and-run accident at night. Two cab companies operate in the city: the Green company and the Blue company. You are given the following facts: 85% of the cabs in the city are …

mathematicsprobability
DEV Community

In This Article The Question The Intuition Trap: Why 50/50 Feels Obvious The Exhaustive Case Proof The Bayesian Derivation The Generalized N-Door Problem Python Simulation: 1,000,000 Trials Business Application: Bayesian Updating Under New Evidence The Question You are a contestant on a game show. In front of you stand three closed doors. Behind one of them is a car; behind the other two are goat…

mathematicsprobability
Towards Data Science

How Knives Out teaches Bayesian thinking (without you realizing it) The post Solving a Murder Mystery Using Bayesian Inference appeared first on Towards Data Science .

aimachine-learningmathematicsprobability
John D. Cook

The function (1 + cos(x))/2 gives a fair approximation to the Gaussian density exp(−x²) You can make the approximation much better by raising it to a power. The function ((1 + cos(x))/2)4 gives a good lower bound and ((1 + cos(x))/2)3.5597 gives a good upper bound. More on that here. There are other ways of […] The post Another Gaussian approximation first appeared on John D. Cook .

mathematicsprobabilitystatistics
PhilPapers: Recent additions to PhilArchive

_Sitting with a Mad Mind : A Working Thesis_. forthcomingCaptured Resonance as Structural Law advances three falsifiable cross-scale predictions. The first — that the kinetics of attractor reconstitution following substrate-directed intervention, normalized for substrate-regeneration capacity, show comparable structural signatures across scales — is the prediction on which the cross-scale identit…

mathematicsprobabilitystatistics
Hot Questions - Stack Exchange
Hot Questions - Stack Exchange
STARS

Statistical modeling of claim severity distributions is central to actuarial science and risk management, where parameter estimation must balance efficiency and robustness. Maximum likelihood estimation (MLE) is asymptotically efficient under correct model specification but sensitive to extreme observations and perturbations from the assumed distributional form. Robust L-estimators, including the…

mathematicsprobabilitystatistics
research.ioresearch.io

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