STATISTICA Blogs

Six years ago today I started my employment at StatSoft.  It was a different era – George W. Bush was in the White House.  We’d never had a female Speaker of the House. Regular unleaded gas averaged $2.95 a gallon and X-Men: The Last Stand was hitting theaters.

What else has changed?

NPR has a pretty neat data visualization on their blog.  The post concerns American women and the job sectors in which they work.  

I’m referring specifically to the set of pie charts in the middle of the post.  Two time periods. Two sexes. Thirteen job sectors.  So much information conveyed in so little space. 

We like math here at StatSoft. When our company posts a geeky link on its Facebook page, a bunch of StatSoft employees will soon ‘like’ it and repost it to their own pages. And you had best bring a pie to share on Pi Day (though this is merely my personal request rather than official company policy).

Of course, love for math is not universal – at least when love is measured by hours spent learning it. 

Last night, I filled in my brackets for the NCAA Men’s Basketball Tournament. I spent more time trying to decide whether VCU would beat Wichita State in the first round than I did actually watching college basketball this year. But I'm not going to let my ignorance stop me from having a good time. To aide in my research, I did what any narcissistic blogger does: consulted the blog post I wrote last year on this subject.

To celebrate Dr. Seuss’s birthday

I thought I’d honor him in a special way.

For Hop on Pop was a first book I read.

And now I read it with my daughter as I put her to bed.

Here is something to make you laugh.

I put his book sales in a GRAPH. 

I love my friends. When they see a nerdy graph or a fun data set, sometimes they’ll share it with me as blog-spiration. 

This is how I became the proud owner of some real-life blood pressure data, as my friend has been requested by their doctor to record this information several times a day. As with any new dataset, I tried out several types of graphs to see which type provided the most useful information. I looked for outliers in the data so that we could investigate and explain them. I also looked for ways to categorize the information in the data set that might help me tease out patterns that are hidden within overall trends. 

Next Sunday, February 5, the New York Giants and the New England Patriots will play in Super Bowl XLVI. I’m not a huge American football fan, but I do typically watch the Super Bowl, just so I can keep up with pop culture and to hear what kind of music the kids are listening to these days.

I took a trip through Super Bowls past on Wikipedia. I played with the data in several ways, but these Categorized Pie Charts were my favorite. I had hoped to make a prediction of who would win the game based on the location of the game, but unfortunately the Super Bowl has never been played in Indiana before.  

Do you ever wake up and say “I want to find some interesting data today”? 

Rather than acknowledge the fact that I might be the only geek here, I’ll just assume the answer is yes.

I knew the monthly jobs report was due out today, but I’ve already written about how “good” job report news isn’t always as positive as it seems on the surface.  

So I looked elsewhere and ended up at the World Bank. I drilled down to the Gender Statistics database and selected all the countries that were available in the list. Two of the interesting items were “Proportion of seats held by women in national parliaments” and “Wage equality between...

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 As a result of the Occupy Wall Street Movement bringing concerns about income inequality to the news cycle, my goal was to find data related to this topic. I didn’t have an agenda, really – I just wanted to be able to confirm or deny whether their claims are legitimate. 

Of course, the data were easy to get. It’s found here at the Census Bureau’s website. It shows mean income for each Fifth of households on an annual basis from 1967 to 2010. All values are shown in 2010 dollars, which adjusts for changes in purchasing power over time. 

 I can definitely relate to the last blog post from my colleague Jennifer Thompson, for I too have a common name for people in my age cohort. I was so tired of having to clarify which Amanda I was that I so desperately wanted to coin the nickname “Shank” for myself. It didn’t catch on for some reason.

You can check out for yourself using Social Security Administration data how common your first name was for US babies born the same year you were. There are 2010 data available as well as yearly data going back to 1880.  Name Voyager is also a fun one to look at for expectant parents and narcissists alike. 

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