STATISTICA Blogs

In large data spreadsheets, it is impossible to view everything at once. Splitting the view of the data into multiple panes can help with tasks such as reviewing and cleaning the data. In STATISTICA spreadsheets, viewing multiple panes within the data is easy.

I just read Amanda's Six Years at StatSoft blog. I have to jump in and say me too. I joined StatSoft in May, seven years ago.

One of my first major projects was for a company (RR)  that creates machines for semiconductors companies. These machines are used in the manufacturing process for chips. They are large, expensive and cut silicon.

Every machine that RR creates has an embeded computer. RR has their own software that runs the machine, but they wanted to provide analytics to their customers. 

So the project started out 

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?

In predictive analytics, several steps are necessary before building models. In addition to understanding the needs and goals of the project, the data should be prepared. Real-world data comes with real-world problems, as I was reminded reading a blog post recently. The success of the project often times is sabotaged by these data issues. So, is your data ready?

Preparing data for analysis is a tricky process. There is no one-size-fits-all way to do things. There are some valid approaches to choose from in the face of various challenges. These challenges include, but are certainly not limited to, missing values, data entry errors, points outside the valid range, outliers, impossible combinations, duplicate records, invariant data, structure and issues of data organization, and the list goes on.  

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Some light reading and Dali art: Kamil Fijorek and Andrzej Sokolowski published a paper in the April 2012 Journal of Statistical Software that introduces STATISTICA's "Separation-Resistant, Bias-Reduced Logistic Regression" macro, which performs Firth-type logistic regression.

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. 

Instrumentation Laboratory, a global medical device manufacturer, faced challenges integrating and accessing data from various systems for quality control of its manufacturing process. The company selected StatSoft's STATISTICA Enterprise data analytics solution to address these issues because Enterprise enables its engineers and managers to collaborate across a common platform, file format, and terminology.

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. 

Son of India, Fan of Sherlock Holmes, Shunner of Cookie-Cutter Solutions: Our Senior Data Mining Consultant Dev Kannabiran riffs on his journey to StatSoft, his predictions of data mining trends, and his love for travel... 

Some plots in statistical analysis require or can benefit from the use of grouping variables or binning of continuous data. The best way to group continuous data will vary by application. This example describes how to group continuous data to meet the needs of your application.