Uncertainty and Statistics

Life is full of uncertainties! It is a fact that weather forecasts for tomorrow are not one hundred percent certain.   No one could ever judge the state of the financial indices tomorrow with one hundred percent confidence.

Business managers often make decisions under pure uncertainties with insufficient data (see Business Statistics section for more details). 

Socio-economic impact modellers have to make life-changing decisions for the society based on potentially uncertain information (Econometrics ).  Because life is uncertain do these professionals leave their decisions to a random choice?  certainly not!

Weather forecasters try to understand and quantify the uncertainty associated with their forecastes. Quantification of the uncertainty is the first step in reducing it. 

This also helps them to assign reliability measures to their day-to-day forecasts. These reliability measures are very important for businesses that crucially depend on daily weather conditions (For example, planning resources for electricity generation for a week in winter).  

Investment specialists often try to estimate financial ratios (for example, p/e) and assign confidence levels to their estimates.   Business managers quantify potential uncertainty in responses  to their decisions so that they could manage the associated risk effectively. Socio-economic modellers always allow room for errors in their not-so-certain decision making processes.

So how do they do it?  They all use tools and techniques based on statistics. Traditionally the term statistics  has been used to refer to the collection and interpretation of data to arrive at conclusions about  unknown parameters.  

Now-a-days statistics means for much more than that. In recent years several techniques have been developed based on the fundamental concepts of statistics to solve scientific and commercial problems.  

In the following we list a few commercial problems and the statistical subject areas that deal with those problems: 1) forecasting solutions - Time Series Analysis; 2) socio-economic issues - Econometrics ; 3) drug development - Clinical Trials; 4) Managerial decisions - Business Statistics ; 5) demand-inventory-supply solutions and corporate performance - Business Intelligence ; 6) financial investment solutions - Financial Mathematics ; and 7) consumer behavior in retail markets - Datamining.

The above list is certainly not complete or comprehensive.   However in this website we plan to provide as much information as possible on the above mentioned topics and on a few more relevant topics. 

This site is designed to be informative to cross-disciplinary university students and research scholars, and anyone interested in dealing with uncertainty problems.  We plan to include more numerical examples to make it interesting and useful for the the high school students too.

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