Day 35 of 1000
I am not one of those guys who hates birthdays and/or their age. I turned 56 on Saturday, a bunch of which I spent driving across the beautiful North Carolina countryside between Raleigh and Charlotte. It rained hard for about forty minutes of a four hour trip in that way that North Carolina’s understand and can handle, but that is completely foreign to us immigrants from the Willamette Valley in Oregon. Still, it was a great trip, especially with my new birthday travel mug (Thank you, Andrew! It really does keep coffee hot for six hours!). Still the rest of the trip was just perfect for driving. The kids worked on homework, slept some, and we talked a lot on both legs of the trip. It was very, very nice.
We went to a church convention. We meet lots of new people at those kinds of events and when people find out that Kelly is a statistics major, they invariably ask here what she will do with a statistics degree. It is a very good question. There are lots of opportunities for statisticians in lots of different fields (bioinformatics, economics, manufacturing, internet data mining, marketing, etc.). The problem is that, in Kelly’s case, this is the wrong question to ask. Kelly studies statistics as a base for a graduate degree. She has no plans to work as a statistician, but views statistics as a hard science degree that provides tools that are useful in whatever other field she might study whether it be marketing, political science, journalism, history, sociology, or any of a myriad of other fields that require statistics for their research.
Our buddy Andrew knows where Kelly wants to go with her degree, so he sent us this link. It is a book about statistics. More specifically, it is a book about how to use statistics in real-world situations. This is exactly what we talked about on our trip. Kelly’s desire is not to be a statistical guru, but to be a guru in some other field that interests here with a profound understanding of the use of statistics in that field. This book shows how to use a set of Python libraries to perform statistical analysis and present statistical data graphically. I downloaded the book, the data sets, and the example programs because it looked so interesting. I think Kelly will continue to work in R as that is a tool more commonly used in her world, but if this book is good enough, I will maybe walk through it with her during the summer.