Introduction to Modern Statistics
This workshop introduces the foundations of modern statistics, including probability, statistical inference, and modeling. Students will learn key concepts and modern techniques in statistics.
Instructor: Wenbin Guo
Term: Winter
Location: Boyer Hall, Room 529
Time: Tuesday to Thursday 9:00 AM - 12:00 PM
Overview
This workshop provides practical training in modern statistical thinking and data analysis. Students will:
- Understand core concepts in probability, inference, and statistical modeling
- Learn how hypothesis testing, permutation tests, and bootstrapping are used in practice
- Gain hands-on experience with statistical analysis in R
- Develop the skills to interpret results critically and avoid common statistical pitfalls
For registration, visit the QCBio workshop page.
Prerequisites
- Basic familiarity with R programming is recommended
Textbooks
- Primary: “Introduction to Modern Statistics” by Mine Çetinkaya-Rundel and Johanna Hardin
- Reference:
- “The Seven Pillars of Statistical Wisdom” by Stephen Stigler
- “Computer Age Statistical Inference” by Bradley Efron and Trevor Hastie
- “All of Statistics: A Concise Course in Statistical Inference” by Larry A. Wasserman
Grading
- Assignments: 90%
- Participation: 10%
Schedule
| Date | Topic | Materials |
|---|---|---|
| Day 1 | Probability and Statistics Basics An introduction to uncertainty and probability, probability distributions, descriptive statistics, and statistical programming in R. | |
| Day 2 | Statistical Inference Introduction to inferential statistics, hypothesis testing, p-values, permutation tests, bootstrapping, and multiple testing correction. | |
| Day 3 | Statistical Modeling Likelihood and maximum likelihood estimation, regression methods, model selection, and common statistical fallacies and pitfalls. |