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A Brief Overview Of Statistics

by: cleopascal on Date: Fri, 18 Feb 2011 Time: 10:48 AM

Statistics is the study, interpretation and analysis of collected data. It’s a science that’s heavy on numbers and calculations. The principles of the field are used in such diverse disciplines as economics, physics, engineering, sociology, politics, marketing and countless others. People who specialize in this particular pursuit are called statisticians.

Statistics are considered a mathematical science instead of a branch of mathematics itself because of its propensity for practical applications. Using survey sampling, data collation and interpretation, it is possible to explain the underlying motivation for past events through statistical analysis. Prediction of future trends can also be made by taking advantage of probability theory.

A mathematician named John Graunt is historically regarded to have founded the science in 1663 with the publication of his theories. Coupled with Pierre de Fermat and Blaise Pascal’s work on probability calculations, these two things laid the foundations for modern statistics during the 17th century.

Modern statistical data collection is generally divided into two categories. These are the methods used in societal, industrial or scientific applications. Organizations would often hire statistical consultants in order to advise them on how to optimize their operations based on the numbers culled from sampling and observing their activities.

Descriptive statistical data collection deals with organizing and presenting observed data into an easy to understand medium. A random subset of a given population is selected for study; this is called the sample. The random nature of the individual components of the sample would make them ideal for observing micro-trends and situations that would be reflected in the macro-community with a fairly high rate of accuracy. The factors that contributed to the trends in the first place can then be deduced and identified. In this way, experiments can be run under manageable conditions that would be applicable on a bigger scale as well.

The statistics data collection experts have collected from the descriptive phase are then applied in inferential statistics. Using this data, predictions for probable future outcomes can be derived. The larger the sample size, the more accurate the forecast model becomes. Correlating relationships between causal elements can be studied for proper exploitation.

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