Statistical Inference via Data Science: A ModernDive into R and the Tidyverse
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Updated
May 15, 2024 - HTML
Statistical Inference via Data Science: A ModernDive into R and the Tidyverse
Code for modelling estimated deaths and cases for COVID19.
My Solutions to 120 commonly asked data science interview questions.
Official AFNI source and documentation
pure-Python HistFactory implementation with tensors and autodiff
MCMC sample analysis, kernel densities, plotting, and GUI
Streamline a data analysis process
A resource list for causality in statistics, data science and physics
Estimagic is a Python package for nonlinear optimization with or without constraints. It is particularly suited to solve difficult nonlinear estimation problems. On top, it provides functionality to perform statistical inference on estimated parameters.
R package for statistical inference using partially observed Markov processes
Basic statistical modelling examples.
Ambrosia is a Python library for A/B tests design, split and result measurement
Using Python, learn statistical and probabilistic approaches to understand and gain insights from data. Learn statistical concepts that are very important to Data science domain and its application using Python. Learn about Numpy, Pandas Data Frame.
Repo for code and small datasets related to Global Policy Lab's COVID-19 policy analysis. Read and share the acompanying article here:
Statistical inference on machine learning or general non-parametric models
Statistics tools and utilities.
My Code Repository for Coursera Data Science Specialization by John Hopkins University
Hypothesis and statistical testing in Python
sub-package of spatstat containing core functionality for data analysis and modelling
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