Introduction to Resampling Methods using R

May 23, 2017

Introduction to the basic concepts and methods of resampling, including monte carlo sampling, bootstrap procedures and permutation (randomization) tests. Topics will include

  • Generating resamples using R
    • Sampling from theoretical distributions
    • Sampling from observed data
      • Randomization between groups
      • Bootstrap sampling
  • Applications
    • Simulations
    • Comparing groups/treatments
    • Contingency tables
    • Correlation and regression
Prerequisites: Knowledge of basic data manipulation and data analysis using R, e.g., the QMS workshop, “Introduction to R for Data Analysis”.

Instructor: Dr. Scott Richter is Professor in the Department of Mathematics and Statistics and Director of the UNCG Statistical Consulting Center. He teaches undergraduate and graduate level courses in statistical methodology, and consults extensively with researchers across campus. More information can be found at

Workshop files:

Resampling Methods Using R











Contact Us

Quantitative Methodology Series

The University of North Carolina at Greensboro
Department of Mathematics & Statistics
116 Petty Building
PO Box 26170
Greensboro, NC 27402-6170

Scott Richter, Ph.D.

Professor, Department of Mathematics and Statistics
Director of Statistical Consulting Center

John Willse, PSY.D.

Associate Professor and Department Chair, Educational Research Methodology