Pinned Repositories
niviz-rater
Simple flexible web application to configure and carry out rating of MR images
CAN-ACN-05-2019
canadian-weather
Explore historical weather data in Canadian cities
covid-19-survey-analysis
Analysis of COVID-19 Survey Data. Demonstration of multivariate analysis and data visualization methods.
explainers
Explainers and slide decks for statistical concepts & methods
niviz-rater
Simple web server to configure and carry out QC of MR images
ontario-electricity-demand-viz
Interactive 3D visualizations of Ontario's market demand for electricity
project-hub
Learn more about projects and their development status here
RMINC-dev
Statistics for MINC volumes: A library to integrate voxel-based statistics for MINC volumes into the R environment. Supports getting and writing of MINC volumes, running voxel-wise linear models, correlations, etc.; correcting for multiple comparisons using the False Discovery Rate, and more. With contributions from Jason Lerch, Chris Hammill, Jim Nikelski and Matthijs van Eede. Some additional information can be found here:
shopify-ds-intern-challenge
Shopify Summer 2022 Data Science Internship Challenge
nathankchan's Repositories
nathankchan/CAN-ACN-05-2019
nathankchan/canadian-weather
Explore historical weather data in Canadian cities
nathankchan/covid-19-survey-analysis
Analysis of COVID-19 Survey Data. Demonstration of multivariate analysis and data visualization methods.
nathankchan/explainers
Explainers and slide decks for statistical concepts & methods
nathankchan/niviz-rater
Simple web server to configure and carry out QC of MR images
nathankchan/ontario-electricity-demand-viz
Interactive 3D visualizations of Ontario's market demand for electricity
nathankchan/project-hub
Learn more about projects and their development status here
nathankchan/RMINC-dev
Statistics for MINC volumes: A library to integrate voxel-based statistics for MINC volumes into the R environment. Supports getting and writing of MINC volumes, running voxel-wise linear models, correlations, etc.; correcting for multiple comparisons using the False Discovery Rate, and more. With contributions from Jason Lerch, Chris Hammill, Jim Nikelski and Matthijs van Eede. Some additional information can be found here:
nathankchan/shopify-ds-intern-challenge
Shopify Summer 2022 Data Science Internship Challenge