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.

# statistics

# Introducing Rank Data Analysis with Arkham Horror Data

## Introduction

Last week I analyzed player rankings of the Arkham Horror LCG classes. This week I explain what I did in the data analysis. As I mentioned, this is the first time that I attempted inference with rank data, and I discovered how rich the subject is. A lot of the tools for the analysis I had to write myself, so you now have the code I didn’t have access to when I started.

# Problems in Estimating GARCH Parameters in R (Part 2; rugarch)

# 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 ) 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.

# 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!

# Materials for Teaching Applied Statistics

Today is the first day of the new academic year at the University of Utah. This semester I am teaching MATH 3070: Applied Statistics I, the fourth time I’ve taught this course.

# Replication Intervals

At the University of Utah I’ve taught MATH 1070 and MATH 3070. Both are introductory statistics classes, but I call MATH 1070 “Introductory Statistics for People Who Don’t Like Math” while MATH 3070 is “Introductory Statistics for People Who *Do* Like Math”, since the latter requires calculus and uses *far more* probability. In both classes, though, students need to learn what confidence intervals (CIs) say and don’t say, and I spend a lot of time debunking common misconceptions for what a confidence interval says.

# Learn Basic Python and scikit-learn Machine Learning Hands-On with My Course: Training Your Systems with Python Statistical Modelling

This post is actually *months* late, but like with my last video course announcement, it’s better late than never. And besides, of my video courses, I had the most fun writing this one.