# Learn Python Statistics and Machine Learning with My New Book: Training Systems using Python Statistical Modeling

Packt Publishing has turned another one of my video courses, Training Your Systems with Python Statistical Modeling, into a book! This book is now available for purchase.

# Introduction

I started my first research project as a graduate student when I was only in the MSTAT program at the University of Utah, at the very end of 2015 (or very beginning of 2016; not sure exactly when) with my current advisor, Lajos Horváth. While I am disappointed it took this long, I am glad to say that the project is finished and I am finally published.

# Introduction

Months ago, I asked a question to the community: how should I organize my R research projects? After writing that post, doing some reading, then putting a plan in practice, I now have my own answer.

# Introduction

Now here is a blog post that has been sitting on the shelf far longer than it should have. Over a year ago I wrote an article about problems I was having when estimating the parameters of a GARCH(1,1) model in R. I documented the behavior of parameter estimates (with a focus on $\beta$) and perceived pathological behavior when those estimates are computed using fGarch. I called for help from the R community, including sending out the blog post over the R Finance mailing list.

# Time Series and MCHT

## Introduction

Over the past few weeks I’ve published articles about my new package, MCHT, starting with an introduction, a further technical discussion, demonstrating maximized Monte Carlo (MMC) hypothesis testing, bootstrap hypothesis testing, and last week I showed how to handle multi-sample and multivariate data. This is the final article where I explain the capabilities of the package. I show how MCHT can handle time series data.

# Beyond Univariate, Single-Sample Data with MCHT

## Introduction

I’ve spent the past few weeks writing about MCHT, my new package for Monte Carlo and bootstrap hypothesis testing. After discussing how to use MCHT safely, I discussed how to use it for maximized Monte Carlo (MMC) testing, then bootstrap testing. One may think I’ve said all I want to say about the package, but in truth, I’ve only barely passed the halfway point!

# My Tutorial Book on Anaconda, NumPy and Pandas Is Out: Hands-On Data Analysis with NumPy and Pandas

I announced months ago that one of my video courses, Unpacking NumPy and Pandas, was going to be turned into a book. Today I’m pleased to announce that this book is available!