Resampling: A Better Way to Teach (and Do) Statistics
Julian L. Simon
(see also vita,
bio,
and writings)
College of Business and Management, University of Maryland, College Park
Introduction
-
- Part I
- First, The Facts of Success, Then the Problem
- Chapter I-1
- The Statistical Results of Resampling Instruction
- Chapter I-2
- On Statistics Teaching, Teachers, and Curricula
- Part II
- Introduction to the Resampling Method As A Tool for Everyday Statistical Work
- Chapter II-1
- First Thoughts About Resampling for Work and Learning
- Chapter II-2
- The Basic Techniques of Resampling
- Chapter II-3
- The Saga of Resampling
- Part III
- On the Teaching of Resampling and Statistics
- Chapter III-1
- A Lesson in Resampling Statistics
- Chapter III-2
- How to Teach Resampling Stats Along With a Standard Text
- Chapter III-3
- On Teaching Resampling as a Basic Tool for Everyday Work
- Chapter III-4
- The Pedagogical Uses of Puzzles
- Chapter III-5
- Pitfalls to Avoid, and Some Practical Tips [under construction]
- Part IV
- The Nature of Resampling
- Chapter IV-1
- Why Statistics is So Difficult, and Why Resampling is Easier
- Chapter IV-2
- Why the Formal Method in Statistics is Usually Theoretically Inferior
- Part V
- Special Topics
- Chapter V-1
- Mathematics and Statisticians
- Chapter V-2
- An Artificial Tutor That Teaches Statistics Effectively
- Chapter V-3
- RESAMPLING STATS Compared to Other Computer Languages [under construction]
- Part VI
- The Future of Resampling
- Chapter VI-1
- Why Johnnies (and Maybe You) Hate Math and Statistics
- Chapter VI-2
- The Future of Resampling Statistics
This page is maintained by Matthew Munsey.
Questions, comments, and/or suggestions should be directed to mmunsey@mit.edu.