Analyse efficacy of your own confidence interval (CI) methods

Generator of new data with the same probability distribution and statistics from a frecuency table or a dataset or or alternatively bothboth.

The ideal way to evaluate binary classification models.

A statistical model of the COVID-19 vaccination campaign. It segments the population into agnostics, pro-, and anti-vaccines. Vaccination is modeled as a Poisson process, and social pressure on the population can change their views on vaccines. The model can faithfully reproduce real-world data.

The purpose of this analysis is to obtain a forecasting model by the relationship between different automobile component combination and their price and predict prices of possible automobile component combination.

Call-center discrete event simulation project mostly done using numpy and simple data structures.

In this repository are contained all the codes for the data analysis of batch accumulation test for PHA production.

Statistical models

A Turkish language model using syllable and character based n-grams (1-gram, 2-gram, 3-gram) built on the Turkish Wikipedia Dump dataset for random sentence generation for NLP tasks and language modeling.

Escrevendo um plugin experimental para interpolação (IDW e Krigagem) no QGIS.

Fantasy National Hockey League Player Performance Predictor. Given the player performance statistics from recent games, various statistical and machine learning models are used to predict player performance in future games for Fantasy Hockey League planning

An analysis of UK greenhouse gas emissions from 1990 to 2023, using ARIMA for time series forecasting, for a task issued by the National Audit Office (NAO). Includes exploratory analysis, stationarity tests, and visualisation with confidence intervals for a 5-year prediction.

Scraping Austrian statistics platform STATatlas for public available data using selenium

NCAA_smalldata_tournamentSimulation

A package for using statistical distributions.

An implementation of latent dirichlet allocation on Wikipedia pages

Predicting House Prices using Machine Learning - Data Cleaning, Feature Engineering, and Model Selection (XGBoost)

python module, showcasing computation (as part of a learning process) of some common statistical methods including mininum sample size, confidence interval estimation methods for mean or proportion, hypothesis testing mehods and regression models witth metrics and test suites

an artificial intelligence project to recognize american sign language

A statistical simulator and calculator to size FIFOs