A curated list of awesome R packages, frameworks and software. With repository stars⭐ and forks🍴
Repository of USC's LA's BEST program. https://lasbest.usc.edu/
The goal is to develop robust predictive models to identify patterns in chronic disease data, aiding public health planning and interventions. This project aims to enhance predictive modeling for chronic diseases, leading to better preventative strategies and health outcomes.
In this project, I explored and analyzed a world population dataset in the R programming language. Utilizing dplyr, tidyverse, and ggplot2, I created two choropleth maps. One map shows the growth rate by continent, and the other shows the growth rate of African countries.
In this repository, software applications in simulation and visualization for various applications are presented with interesting examples.
R code for the PBS users for generating and working on the PBS clusters
a Bellabeat product and analyze smart device usage data in order to gain insight into how people are already using their smart devices.
Solutions to "Advanced R" (2nd ed.) exercises (unofficial) 📖✍️
Elements of Survival Analysis in R and Python
This repository is designed to provide a comprehensive introduction to R programming, tailored for data analysis and statistical computing. It includes a collection of tutorials, examples, and exercises that guide users through fundamental R concepts, data manipulation, visualisation, and advanced techniques.
Here is a whole bunch of genomic data analyses using Bioconductor packages. The files are found in the form of .R files.
Analysis of global sunspot numbers spanning from 1700 to 2023, featuring forecasts derived using a SARIMA model
This repository is a collection of various data science projects undertaken for exploration and learning purposes.
Using R programming languages we perform some experiment which can be used by students.
Identifying socio-economic factors that contributed to Covid_19 deaths. A Dataset was created through an SQL JOIN of data gathered from NOMIS website and the data on number of Covid_19 deaths as published by the NHS in UK.
using R programming to design a model that predicts churn.
Este projeto utiliza análise Bayesiana para modelar o preço de venda de carros com base em diversas variáveis, como ano de fabricação, quilometragem rodada e tipo de transmissão. Após a leitura e limpeza dos dados, o modelo de regressão é construído utilizando amostragem MCMC para obter distribuições posteriores dos parâmetros.
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