Minimizing Risk in Decision Making

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Usual Analytical Method

Statistics employs the least squares algorithm to calculate a mathematical best fit for functions (Linear, Polynomial, Sinewave, etc.) we guess a priori to represent the data structure. This method, Regression Analysis, only applies to data of one or two data types (Price vs. Time, etc.). Multiple Regression, the next higher level statistical tool, is used to discover order in data of more than two data types.

Although Regression Analysis is widely applied, the hidden assumption that mathematical functions can describe all real data generally remains unchallenged.

Our Approach

The real world is complex and nonlinear. However, because hidden order is embedded within complexity and nonlinearity, it can only be discovered using tools that neither assume linearity nor apply mathematical functions.

Scarce Ideas™ uses proprietary technology to analyze (discover order) and recognize (categorize) all patterns in real data. Examples of the diverse problems and data types are:

• Risk - Ratings (Personnel, Products, Services, Real Estate, Cars, ...)
• Risk - Financial (Oil Well Logging, Insurance, Loans, Ventures, ... )
• Risk - Medical (Monitor Health, Glaucoma, Skin Anomalies, ... )
• Risk - Engineering (Flight Safety, Process Monitoring and Management, ... )
• Risk - Marketing (Existing Needs/Products, New Products, ... )
• Risk - Legal (Passport Control, Prisoner Probation ... )
• General Categories (Characterize Salmon Herds, Predict Earthquakes, Discover Planets, ... )

Notes/Demos

This page will be updated as necessary.