This is a repository for resources completed as part of the Duke University Statistics with R Specialization.
To be successful in this specialization, learners have analyzed and visualized data in R and created reproducible data analysis reports, demonstrated a conceptual understanding of the unified nature of statistical inference, performed frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions, communicated statistical results correctly, effectively, and in context without relying on statistical jargon, critiqued data-based claims and evaluated data-based decisions.
Course Link:
https://www.coursera.org/specializations/statistics
Modules:
01: Introduction to Probability and Data with R
02: Inferential Statistics
03: Linear Regression & Modeling
04: Bayesian Statistics
05: Statistics with R Capstone
Instructors:
Mine Çetinkaya-Rundel, David Banks, Merlise A Clyde, Colin Rundel