Evan Miyakawa

Evan Miyakawa

Statistics Ph.D. Candidate

Baylor University


My name is Evan Miyakawa, and I am a 4th year Ph.D. student in Statistics at Baylor University. I obtained my Masters degree in Statistics from Baylor in 2018. I previously received my bachelors degree in Mathematics from Taylor University in 2017. In my spare time, I run a college basketball analytics website at https://evanmiya.com.


  • Statistical Computation Methods
  • Bayesian Statistics
  • Statistical Machine Learning
  • Big Data
  • Sports Analytics


  • Ph.D. in Statistics (still in program), 2020

    Baylor University

  • M.S. in Statistics, 2018

    Baylor University

  • B.S. in Mathematics, 2017

    Taylor University














Graduate Assistant

Baylor University

Aug 2019 – Present Waco, TX
My graduate assistantship included statistical consulting with various projects at Baylor, including a (soon to be published) paper implementing the recycled predictions bootstrap method with professors in the Economics and Health Services Research departments. I am also involved in classified consulting work for Eli Lilly and Company’s statistics department.

Chief Data Wrangler

Wakefield Research Partners

Jun 2019 – Present Waco, TX
I provide company-wide technical support in R, and I automate data generation processes.

Introduction to Statistics Teacher

Baylor University

Aug 2018 – May 2019 Waco, TX
I taught two semesters of Introduction to Stats for undergraduate students. I also tutored students studying statistics at the undergraduate and graduate levels.

Data Analyst Intern

Global Media Outreach

Jun 2016 – Aug 2016 Plano, TX
I conducted statistical analysis and provided reports on the effectiveness of advertisement campaigns, the performance of online communication volunteers, and donation trends. My research on advertisement campaigns led to over $40,000 saved by the organization in just two months.

Papers and Presentations

TRICARE for Life: The Impact of Reduced Cost-Sharing on Health Care Use

This paper is being submitted for review, co‑authored by Dr. Forest Kim and Dr. Neil Fleming at Baylor University. I contributed to this paper by applying the recycled predictions bootstrap method in order to find the impact of a policy change on expenditures for patients of various health insurance types.

Bayesian Computational Strategies - Preliminary Dissertation Presentation

I presented a talk on common Bayesian computational methods and implementations, which contrasts each and gives general guidelines for use. The paper form of this presentation is being written and will be a chapter in my dissertation.


  • Gives overview of Gibbs Sampling and Hamiltonian Monte Carlo methods.
  • The presentation addresses strengths and weaknesses of STAN, JAGS, OpenBUGS, Nimble, and Greta, and compares their respective computation time and accuracy.