STATISTICA Blogs

Recently, I sat down with Gary Miner to understand why and how he uses STATISTICA.

 

 

 

 

 

 

Largest international survey of data mining practitioners reports highest levels of adoption of and satisfaction with StatSoft’s STATISTICA software.

Each time we build a better mouse trap, those darn mice get a little smarter. Finding what distinguishes the fraudulent claims from the legitimate ones can be a difficult process. Statistical and data mining models can be used to estimate the likelihood that a claim is fraudulent.

Text Mining enables you to harness valuable information that was previously unusable for building a better mouse trap, a high powered predictive model. In this video, we will explore a case study where the task at hand is predicting fraudulent automotive insurance claims. Predictive accuracy was relatively good before. Adding results from text mining helped this company to catch 10% more fraudulent claims while simultaneously reducing the false positive rate. 

 

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Histograms visually show the frequencies of data. Similarly, a bivariate histogram shows frequencies across two variables.

 

Hurwitz’s Victory Index Labels StatSoft as “Double Victor”

 

 

 

In a review of STATISTICA 10 in Scientific Computing by statistician Dr. John Wass, the author says “[the] Data Miner product contains all of the routine and advanced statistical tests, as well as a number of very sophisticated mining routines. All of this is still wrapped in a very straightforward and, in my opinion, simple user interface.”

Dr. Wass then walks the reader through analyzing a common problem in response optimization.

Dr. Wass concludes by stating “It is very difficult to do justice to software of this breadth and depth in a short review. Since the program is now exceedingly ‘bulked up’ with data mining capabilities, the power is immense.”

Read the full report >>

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