An Introduction

The first statistics class I took was a disaster. Held in a large auditorium packed with students, its atmosphere was more “refugee camp” than classroom. The general din made it impossible to hear the professor. Attendance was mandatory and, as far as I could tell, the sole determination of our final grades. One day a group of students started punching each other, hard. A fight had broken out. That’s right, a fight had broke out in my graduate level statistics class.

I quickly gave up on learning anything from the lectures and turned to the $150 textbook instead. However, it was a collection of random SAS code and ANOVA tables, and the examples didn’t look like anything I had seen before. I re-read the chapter on t-tests 50 times before giving it up as a lost cause. Even basic concepts, like “average”, became confusing. Everything was backwards.

Despite the rough start, I love statistics. Statistics create knowledge. You start with a pile of numbers, you run statistics on them, and out comes information for making the best decisions. That’s cool, right? Making an informed decision is so much more awesome than guessing, especially when it pertains to how to use precious resources, like our time. It’s awesome. Stats are also fun. That’s right, stats are fun. You might now believe me yet, but you will. Trust me.

With this blog, I am going to explain statistics so that you can use them confidently. If you’re in the middle of a statistics jungle, and fights are breaking out around you, I want this blog to be a refuge so that you can learn what you need to learn. The methods can be used in a lot of contexts, but, because I work in a mouse molecular genetics lab, I’m going to explain them primarily within that context. I’ll try to keep things general, so that if this isn’t your specialty you can still follow along, but I wanted something that my co-workers could turn to and understand without having to translate the examples into their own language. Thus, examples will be given in terms of “gene expression” rather than “migrating birds”, or “seismic activity”.

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