Statistics is a branch of mathematics that deals with obtaining, ordering and analyzing a set of data in order to obtain explanations and predictions about observed phenomena.
Statistics consist of methods, procedures and formulas that allow information to be collected and then analyzed and extracted from it relevant conclusions. It can be said that it is the Science of Data and that its main objective is to improve the understanding of the facts from the available information.
The origin of the word statistical is usually attributed to economist Gottfried Achenwall (Prussian, 1719-1772) who understood statistics as “science of things that belong to the State.”
Transversality of statistics
One of the fundamental characteristics of statistics is its transversality. Its methodology is applicable to the study of various disciplines such as: biology, physics, economics, sociology, etc.
Statistics help to obtain relevant conclusions for the study of all types of agents such as: humans, animals, plants, etc. It usually does it through statistical samples .
Branches of statistics
Statistics can be subdivided into two main branches: descriptive and inferential.
- Descriptive statistics: Refers to the methods of collection, organization, summary and presentation of a data set. It is mainly about describing the fundamental characteristics of the data and for them, indicators, graphs and tables are usually used.
- Inferential Statistics: This is a step beyond mere description. It refers to the methods used to be able to make predictions, generalizations and obtain conclusions from the analyzed data taking into account the degree of existing uncertainty.
Inferential statistics are further subdivided into two main types: parametric and non-parametric statistics.
- Parametric statistics:It is characterized in that it assumes that the data have a certain distribution or specify certain parameters that should be met. For example, in a parametric analysis we can work under the assumption that the population is distributed as a Normal (we must justify our assumption) and then draw conclusions under the assumption that this condition is met.
- Nonparametric statistics: It is not possible to assume any underlying distribution in the data or a specific parameter. An example of this type of analysis is the binomial test.
Example of the use of statistics in economics
Statistics is widely used in economic analysis. It helps us to verify the application of economic theory in practice. Some examples of the use of statistics in Economics are:
- Development of aggregate macroeconomic indicators.
- Predictions about the future behavior of the demand.
- Test the validity of hypotheses based on economic theory.
- Calculate the unemploymentrate .
- Organize and present economic data such as: price developments, GDP, etc.