BLOG PROGRESSIONHere's the basic progression of the blog:
- My first post set out my original intention for this blog in December 2014. Essentially, a super nerdy place for me to talk about the challenges of managing a data science team, writing code, and dealing with an R production server.
- The blog proceed this way, gaining a small following through January thru March, with readership generally tripling each month. With a higher readership in March, I bought this domain, and moved off a blogger subdomain.
- About this time, I noticed that the analysis posts (where I analyze actual data) were doing much better than the conceptual posts, where I talk about data science in general. So I moved this way, posting about analyses about things that annoy me in the media. This also led me to post more about going-ons data-wise in my home state of Kansas.
- Move on to the present day: I've posted about 90 times on the blog, have a fairly large readership (still growing each month), and have setup a Twitter account specifically for the blog.
"BEST OF"Here are the most read blog posts from this blog:
- My Data Science Toolkit. This super-nerdy post was shared a lot when first released, and continues to be very popular among the data science community.
- Kansas Election Fraud. This post is my first take on Beth Clarkson's analysis of Kansas voting records. This has seen some renewed interest, as it is making news again this week.
- On Weird Metrics. This is the first post to get a large viewing on the site, largely from being picked up by John Durant, a major figure in the "paleo" movement. This post also proved that showing a sense of humor is a great way to increase views.
- Sales Tax. This wasn't really a data science, or even a statistical analysis, but simple math. Effectively, I was just looking at how Sales Tax impacts people differently than increases to income tax.
- Teacher Salaries. Annoyed at the bad data passed around by multiple Kansas entities, I found some legitimate data, then controlled it for cost of living so we could make legitimate comparisons to other States.