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Think Stats

2/27/2014

5 Comments

 
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Last week, I finished plowing through Allen Downey's Think Stats. It took me about 5 days to work through it cover-to-cover. This book is great for those who need a crash course in using Python to do statistics. The conceit of the book is that it's a stats book for programmers. Hence, the statistics in it aren't past an upper-lever undergraduate level in difficulty. However, the programming required to work through the problems is at a higher level than I have seen in any other introductory stats book. I found it to be a great way to improve my Python programming. I worked through about 80% of the examples, skipping only those that were either trivial or did not seem relevant to my learning goals. For many of the examples, Downey provides .py files you can download from the book's website. I found that I usually took a different approach to solving problems than he did, but we most often agreed on the solutions. 

Anyway, the book is available as a free download and worth the time.

5 Comments
Flavin
2/27/2014 10:06:05 am

Was your primary pedegogical goal the stats or the python? And why?

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Ben link
2/27/2014 12:04:45 pm

A combination of both, but I already knew most of the stats. There were a few distribution in there I did not know, but most of the rest was straightforward. I wanted something more complicated that CodeAcademy for Python as well.

I interviewed at Allstate in Chicago this week for an associate data scientist position and was preparing for that. I think I did alright on the interview considering I taught myself most of my programming and stats knowledge.

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Flavin
2/27/2014 10:19:53 pm

I found card game simulations to be a good way to teach myself python, or to keep my skills sharp. The stats are pretty simple, so it might not help much there. But it can give you a project with a clear goal and scope, which is nice.

Recommended first project: distribution of first clubs in Schuster-rules Spades.

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Ben link
2/27/2014 11:44:30 pm

I was also using Python for chessboard stuff. I thought the stats would be a good way to prepare for Data Scientist interview. It took a while to figure out, but I think that's what I want to be when I grow up. I hope I get the damn job I interviewed for this week because I'm tired of looking/applying for jobs. Also, it's a really cool job.

I'm taking a pretty simple Data Analysis and Statistical Inference course on Coursera at the moment that's teaching my some R. I have to do a project for the course and because of the data set I choose (UFO sighting data), I need to write a program to scrape the data off the webpages. There are too many different pages to do it all by hand. I think that will be a great exercise too.

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