Statistics – Concept, levels, history, importance and branches

We explain what statistics is, its measurement levels, history, branches and its importance. Also, differences with probability.

Statistics is the science of data management.

What is statistics?

Statistics is a formal and deductive scientific discipline, often considered a branch of mathematics, which study variability and the laws of probability, through various tools, both conceptual and sampling.

The field of statistics includes the necessary methods and procedures to collect information about reality and organize, contextualize and classify it in order to obtain viable conclusions, expressed mathematically. It can be said that it is the science of data management.

In this way, statistics contemplates four levels of data measurement, known as statistical measurement scales, which are:

  • Nominal, which describes variables whose difference between them lies more in quality than in quantity.
  • Ordinal, which describes variables on a continuum in which their values ​​can be ordered, that is, assign a hierarchy or an order to the data.
  • Interval, which describes variables whose values ​​establish recognizable ranges.
  • Rational, which describes variables with equal intervals and that allow an absolute zero to be placed, in such a way that it represents the absence of characteristics.

Although statistics is a field of study in itself, it is characterized by its transversal nature, that is, by serving as a tool for many other disciplines and sciences, regardless of their specific fields of knowledge: biology, economics, demography , and so on.

History of statistics

The antecedents of statistics abound in Antiquity, especially when the first great empires with large populations arose, such as Babylon, Egypt or China, in which the need to count the population and obtain relevant information for the State, regarding the collection of taxes and other similar matters.

Nevertheless, the first recorded methods of calculating probability appear in the correspondence between Pascal and Pierre de Fermat in 1654. On the other hand, the first scientific treatments of the matter are by Christian Huygens in 1657, as well as the works Ars conjectandi by Jackob Bernoulli in 1713 and Doctrine of possibilities by Abraham de Moivre in 1718.

Formally, statistics emerged in the 19th century, when it was recognized as the discipline that studies the ways to collect data and information. The term had already been coined by the Prussian economist Gottfried Achenwall (1719-1772), who had proposed it as the “science of state affairs”, that is, Statistik, translated into English as “political arithmetic.”

Although Achenwall is recognized as the father of this discipline, its implementation in other areas of human life is due to the Scottish agronomist John Sinclair (1754-1835).

Since then, the study of statistics and probability has been incessant. One of its contemporary pivotal moments took place at the beginning of the 20th century, when Francis Galton and Karl Peterson transformed their field of study, bringing mathematical rigor and applying it not only to science, but to politics and manufacturing.

Importance of statistics

Statistics have immense relevance in the modern world, which transcends the specific organizational needs of the population that states have. The latter, however, linked to control and decision-making, as well as the implementation of public policies, are fundamental matter for approaching the thinking and way of life of the populations.

But statistics too serves as an information processing tool for many disciplines, both from the natural sciences and from the social sciences, since it allows to collect information regarding objects of any nature.

Branches of statistics

Statistics, broadly speaking, contemplates two well differentiated branches:

  • Descriptive statistics, dedicated to the visualization, classification and numerical or graphic presentation of the data that emerged during the study. Its objective is to facilitate the handling of large volumes of data, such as occurs in population pyramids, histograms or pie charts.
  • Inferential statistics, dedicated to generating models and predictions from the studied phenomena, taking into account their randomness dynamics. Through these mathematical models it aspires to find useful conclusions or forecasts that transcend the scope of the merely descriptive.

Statistic and probability

Both statistics and probability are dedicated to the scientific and formal study of chance, but they do so from two different points of view:

  • Probability, on the other hand, it is dedicated to the comparison of the frequency with which an event occurs, as long as it depends on chance, in search of recognizable patterns that allow making concrete predictions.
  • StatisticsInstead, it tries to draw conclusions from random facts, observing them until it finds the laws that define them and, therefore, allow them to be interpreted.