An Introduction

Where the love affair began - Carnegie Mellon University

It was during my junior year of college, when taking a class in basic statistics for the Engineering and Public Policy half of my double major, that I fell in love with the representation of behavior and phenomena by numbers. First it was hypothesis tests that could actually tell if a difference was statistically significant or not. I don't know why it fascinated me so much, but I found such beauty in being able to prove with numbers whether I was seeing a real difference in two sample populations. It then moved on to the assumptions and requirements for statistically correct regression models. All of a sudden, Excel graphs and their regression functions were to be used only by those who didn't know better. It made me so happy that I took several more classes in statistics.

I started my career as a design engineer at Ford a few years later. I focused on my engineering career, dabbling in statistics occasionally during my masters degree. A lull five years into my engineering career led to an opportunity to complete Six Sigma Black Belt training and certification at Ford. Over the course of a year I completed five projects at Ford, realizing more than $5 million in hard and soft savings. I rediscovered my love for statistics. Statistics had allowed our project teams to see solutions that we wouldn't have otherwise seen. More importantly, I learned the key to statistics: they are useless unless you have enough of a foundational understanding of a topic to ask the right statistical questions.

And that's what has inspired this blog. I plan on approaching statistics as a tool to answer questions that I have already asked myself. I will not search for random patterns, but instead pose hypotheses based upon reasonable expected potential behavior and seek to prove or disprove those hypotheses via statistical analysis. I will not take the approach of the authors of Freakonomics, seeking random behavior in patterns of numbers for shock value. Rather, I will take the approach of the authors of Soccernomics - I will attempt to answer questions that have much emotion surrounding them but have had little data applied to them during the endless, heated debates.

(Quick sidebar: If you listen to one thing I say on this blog, it is this - READ SOCCERNOMICS. If you like soccer and/or statistics, you will love the book. It is chock full of real, data driven soccer knowledge that cuts through the "tribal knowledge" that turns out to just be tribal)

I may not always be right, but I will go where the numbers lead me. I will always try to give enough of the statistics theoretical background so that readers can understand the relative strengths and weaknesses of the analysis method used. Most of all, I will try to be clear in my presentation of my hypotheses prior to conducting any analysis. I may not be the most prolific blogger, but the posts I do make will be full of analysis that is statistically correct and way more useful than the statistics you find on ESPN's Soccernet.

I hope that you find this blog interesting. It is a passion of mine that I hope to communicate to you.