Resources
"It's a surprising, and crucial aspect of statistical theory that the same data that supplies an estimate can also assess its accuracy" Bradley Efron (in his book, Computer Age Statistical Inference)
Achieved Graduate Statistician(GStat) status on January 13, 2020.
"It's a surprising, and crucial aspect of statistical theory that the same data that supplies an estimate can also assess its accuracy" Bradley Efron (in his book, Computer Age Statistical Inference)
Here you will find links to some good lecture notes, writing aids and my comments on some textbooks etc. that I have come across.
Disclaimer: I do not own rights to this. They are provided freely online by the respective Instructors. Hence, some of the links probably may not work anymore.
A must have book! Computer Age Statistical Inference by Bradley Efron & Trevor Hastie
Introduction to the Theory of Statistics by Mood, Graybill & Boes. This book is quite old but contains the goodies for mathematical statistics at the graduate level . I have had the opportunity to read the 3rd edition book from cover to cover and I love the way the authors presented the material especially ideas on Estimation & Hypothesis Testing.
How to be a modern scientist by Professor Jeffrey Leek. A must-have for any graduate student. Hear from Jeff himself
"The face of academia is changing. It is no longer sufficient to just publish or perish. We are now in an era where Twitter, Github, Figshare, and Alt Metrics are regular parts of the scientific workflow. Here I give high level advice about which tools to use, how to use them, and what to look out for. This book is appropriate for scientists at all levels who want to stay on top of the current technological developments affecting modern scientific careers."
Lecture Notes
Asymptotic Tools by Professor David Hunter. Notes are good for Asymptotic Statistics (Large Sample Theory) class.
Preparation for Statistical Research by Marie Davidian. Here you find an organized introduction to the necessary skills and knowledge for a career in statistical research (Thanks, Dr. Olbricht for pointing this great resource to me).
Probability and Mathematical Statistics by Professor Joshua Tebbs. I have benefited immensely from Prof Tebbs elegant notes. I sent him a "thank you" email some time back.
Writing aids
A course in mathematical writing by Donald E. Knuth, Tracy Larrabee & Paul M. Roberts
How to write mathematics. Tips on technical writing from the Mathematics Handbook at Trent University
Advice on the presentation of statistical results, from an AmstatNews article.