Bernoulli Trials- Biased & Unbiased Coin Flips - Uniform Distribution
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Updated
May 12, 2018 - M
Bernoulli Trials- Biased & Unbiased Coin Flips - Uniform Distribution
Fast Generation of Random Numbers by Sampling Properties of Particles at Equilibrium
German Tank Problem
Write a program (in your favorite language) to obtain N samples from each of the following distributions: (i) Bernoulli with μ = 0.5; (ii) Poisson with parameter λ = 5; and (iii) Uniform on [0, 10].
Provide true random numbers based on the random-bit file generated by RANDOM.ORG
Get an integer between a min and max, bring your own random number generator.
Enthält statistische Tests auf Gleichverteilung und Monte-Carlo-Simulationen um diese zu vergleichen.
Brief into about Central Limit Theorem (CLT) and Python code for finding mean of CLT and plotting using seaborn and matplotlib on normal, uniform, multi-nomial distribution.
Estatística, Modelos de Probabilidade Contínua, Modelos de Probabilidade Discreta, Distribuições de Probabilidade, Média de um dataset
Normal Distributions,Uniform Distributions and Poisson Distribution with the help of Python Modules
Learning Reliable Rules under Class Imbalance (SDM 2021)
PyPi package for modelling Probability distributions
[Python] Explored different Multiarmed Bandits algorithms to find the best election campaigns more effectively
Position prediction of invisible tree using EM algorithm of GMM. We used Python's Matplotlib data visualization and preprocessed to determine the fruit distribution. BIC and AIC indexes were used to determine the number of cluster categories, and Gaussian mixture model was used to cluster according to the fruit data to predict the coordinates o…
Probability distribution simulator for Poisson distribution, exponential distribution and uniform distribution
Statistics library for Dart
Any Random (Number , String , Password, Dice, Card, Gaussian Number, Uniform Number, Time, Date) Generator
Seedable pseudorandom number generator (PRNG).
A MATLAB project which applies the central limit theorem on PDFs and CDFs of different probability distributions.
Visualization of Mass Redististribution and Tranport.
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