Play-By-Play NFL Data
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Updated
Jan 2, 2014 - HTML
Statistics is a mathematical discipline concerned with developing and studying mathematical methods for collecting, analyzing, interpreting, and presenting large quantities of numerical data. Statistics is a highly interdisciplinary field of study with applications in fields such as physics, chemistry, life sciences, political science, and economics.
Play-By-Play NFL Data
Scripts + data to recreate analyses published on http://benjaminlmoore.wordpress.com and http://blm.io
My main class notes when i study in statistics for a master in university of Glasgow
some quickly written examples of workflow in R and RMarkdown
Data Science Capstone by Johns Hopkins University: Predictive Text Model
R exercises for statistical data analysis class.
Course Materials for STAT 385: Statistical Programming Methods Spring 2017
Bioinformatics workshop on Data management, analysis and visualisation
Python modules and IPython Notebooks, for the book "Introduction to Statistics With Python"
Some visualizations for Math352 Undergradutate Probability and Statistics
Information about and materials for graduate course "Logic of Quantitative Research in Political Science" at the University of Copenhagen, February 6-10, 2017
This is the shared repository for STAT 537 class at The University of Tennessee, Knoxville.
Advanced R Statistics, forked from selva86/selva86.github.io See https://selva86.github.io
Introduction to Open Data Science exercises
Predicting the winners of Miss Finland 2016 with penalized logistic regression, using image data.
This repository will be containing all my projects submitted during Data Analyst Nanodegree program
Final project for course Introduction to Open Data Science