# Who Survives Riddler Nation?

## Introduction

Last week, I published an article on learning to fight in the Battle for Riddler Nation. Here’s a refresher of the rules:

In a distant, war-torn land, there are 10 castles. There are two warlords: you and your archenemy. Each castle has its own strategic value for a would-be conqueror. Specifically, the castles are worth 1, 2, 3, …, 9, and 10 victory points. You and your enemy each have 100 soldiers to distribute, any way you like, to fight at any of the 10 castles. Whoever sends more soldiers to a given castle conquers that castle and wins its victory points. If you each send the same number of troops, you split the points. You don’t know what distribution of forces your enemy has chosen until the battles begin. Whoever wins the most points wins the war.

# The End of the Honeymoon: Falling Out of Love with quantstrat

## Introduction

I spent good chunks of Friday, Saturday, and Sunday attempting to write another blog post on using R and the quantstrat package for backtesting, and all I have to show for my work is frustration. So I’ve started to fall out of love with quantstrat and am thinking of exploring Python backtesting libraries from now on.

Here’s my story…

# Where to Go from Here? Tips for Building Up R Experience

At the University of Utah, I teach the R lab that accompanies MATH 3070, “Applied Statistics I.”” None of my students are presumed to have any programming experience, and they never hesitate to remind me of that fact, especially when they are starting out. When I create assignments and pick problems, I often can write a one- or three-line solution in thirty seconds that students will sometimes spend four hours trying to solve. They then see my solution and slap their foreheads at its simplicity. I can be tricky with my solutions. For example, suppose you wish to find the sample proportion for a certain property. A common approach (or at least the one used in the textbook our course uses, Using R for Introductory Statistics by John Verzani) looks like this:

# Is Hillary Clinton a Progressive? An Investigation Using Statistical Methods

There was once a time where only the most extreme leftists would accuse Hillary Clinton of not being a true progressive, prior to, say, 2008. Even after 2008, Hillary Clinton was seen as perhaps being a more moderate Democrat, but still, ultimately, a progressive. Republicans certainly would call Clinton a leftist and still continue to believe so.

# How the House Makes a Profit: A R Shiny App for Explaining the Key Idea to Gambling

As many of you may know, I teach statistics at the University of Utah. Below is a post about how industries based on chance events, such as casinos or insurance companies, are able to guarantee a profit. I have also included R code for a Shiny app that demonstrates the ideas discussed in the blog post.