# Bayes’s Theorem: Part II

We left off last time with the statement of Bayes’s Theorem. Let’s walk through this equation.

# Bayes’s Theorem: Part I

On a Friday afternoon in 1989, the physicist Leonard Mlodinow got a phone call from his doctor. His doctor told him there was an over 99 percent chance that he was infected with HIV.

The doctor was wrong. Not only was the physicist HIV-free, the chances that he was sick had really been less than 10 percent.

The doctor had done his medical testing perfectly. He just messed up the statistics.

In particular, he failed to use Bayes’s Theorem.

# What is Math Research?

This is a short post on something that I get asked a lot: What is “math research”?

# My Top Three Books for Quantitative Thinking

In many a high school math class, one student raises his hand and asks, “Why do we need to know this?”

Sometimes a teacher responds, “Because math teaches you how to think.”

Leaving the strengths and weaknesses of that answer aside, let’s talk about some books that can teach you something about how to think.

You won’t see many topics from your high school math classes in these books. but all of them deal with quantitative concepts. What’s more, all have helped me understand the world more clearly.

# Happy Pi Day!

Most people have heard about π at some point, but I thought I’d talk a little bit about how I think mathematicians think about π.

# What Are Odds? Part II

In the last post, we discussed a suggestion for what probability means. But extending that interpretation to an election is a stretch. In the context of elections, makes more sense to talk about probability from another perspective.

# What Are Odds? Part I

Three days before the most recent presidential election, two forecasters got into a statistics fight on Twitter. They both thought the same candidate would win. So what were they arguing about, exactly?

# On Explaining

I just watched two YouTubers explain binary. To me, one video’s explanation was fine, but the other was great. I’m still pondering this, and I’d like hear your input!

# Lessons From Go Fish

On a family vacation in the Rocky Mountains, my siblings decided to play Go Fish. My brother made a rule: if anyone gets dealt three of the same card (like three 8’s), return your cards and shuffle the deck. My hunch was that a triple isn’t actually so rare. So what are the actual odds of getting a triple if the deck is shuffled randomly? How would you go about figuring that out?

# You’re Not Bad at Math

Even if you hate it. Even if you flunked it in high school.