A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.
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Updated
Nov 7, 2024 - Python
A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.
Shiny App for comparison of samples
PlotTwist - a web app for plotting and annotating time-series data
A MATLAB package for multivariate permutation testing and effect size measurement
Case Studies and Projects in Machine Learning/EDA/DL
🏠 This repository contains data analysis scripts for the 2022 American Community Survey (ACS) focusing on individuals aged 25 and over in North Carolina, based on 75,340 observations. This repository offers valuable insights into demographic and economic patterns across North Carolina's urban areas.
Linear Regression with errors in both X and Y, correlated or not, confidence intervals and plots.
Free WordPress Plugin: This sample size calculator enables you to calculate the minimum sample size and the margin of error. Learn about sample size, the margin of error, & confidence interval. www.calculator.io/sample-size-calculator/
A comprehensive module used to calculate the high bound, low bound, and center of a Wilson score interval.
Utility functions for statistical population samples.
about statistical techniques for Data Science
MSc Dissertation: Estimating Uncertainty in Machine Learning Models for Drug Discovery
More Meaningful Measurements: Effect Sizes and Confidence Intervals for Proportions using Python
Testing hypothesis and building Confidence Intervals
Use bootstrap resampling to estimate the sampling distribution of a statistic
Package provides python implementation of statistical inference engine
Basic Statistic operations using R language
Had the incredible opportunity to present at the Don Bosco 1st International Conference near Sukhdev Vihar Metro on 27th July, 2024! 🎤🗓️, and My 2nd International Confrence so Far 😉
The fifth project from a Data Scientist with Python track by DataCamp
Calculate confidence intervals for correlation coefficients
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