Introduction
The concept of Statistics, nowadays, remains a long time ago. It represents a discipline (science) just like any other, but unlike for some, it is a branch of mathematics for others a field in its own right. This famous expression, however, was born in the 16th century (1771 in French, 1798 statistics in English). Etymologically, it derives from the expression in Latin called "status" (state). Notwithstanding, its implementation starts from 3000 BC by the collection of observations (census) on people or materials in order to allow the public decision-maker to be able to know more their power or their evolution in a specific field (example : Mesopotamia). In addition, Wilcox (1935) identified more than a hundred definitions of the notion of Statistics. It is clear how much this concept divides the opinions of the scientific community, which remains as puzzling as we imagine. In this circumstance, Kendall pointed out that this was one of the things that statisticians seem more than ever to oppose about the conception of statistics. In addition, the most accepted definition appeared in 1982, announcing that Statistics is a set of methods whose purpose is to collect, process, interpret and disseminate statistical data. In general, it is a science that is simply dedicated to data otherwise-says a data science (data science in English). The statistics (in particular a statistic) represent the processes by which we study a set of observations (people, materials, natural phenomenon, human behavior, chemical species, plants, animals ... etc. These are methodical approaches or Mathematical magnitudes (statistical tools) All the more so, John Tukey considers the ramification of statistics in two approaches that intertwine: exploratory statistics and confirmatory statistics From a general point of view, Statistics is subdivided into two sections namely the Descriptive and inferential statistics: The first one allows the data to be put in place (census or sampling) then the one-dimensional and multidimensional study of the studied and collected characters on the observations (forecast, Data Manning, regression, correlation ...). The second is more concerned with generalizing with a margin of error (extrapolation) the information deduced from a representative sample on the entire population. To find this information in a very complex environment, both mathematical and computer approaches are sought. Often, various trends in the field of Statistics are suggested. In my opinion, it is primarily at the service of public decision-makers, research and teaching.I. Descriptive or exploratory statistics
One of the essential roles of statistics is the ability to extract vital information in a complex and structured database, which is not easy with a simple reading. The tools by which one manages to do it are various, some are called parametric and others non-parametric. It is essential to distinguish between two methods of descriptive statistics which consist of facilitating information on a set of observations. They may be synthetic quantities or summary figures on the characters studied. Let's take a one-dimensional approach to variables. I define it as the speculation in a two-dimensional space of the position of each observation with respect to a super-point (center of gravity) and on the other hand a grouping according to a specific criterion. Nevertheless, the link between two variables is even more important because of its consideration beyond the limited scope of the first analysis. The dependence, the strong connection or the causality between two variables makes a judgment on the link between two different characters observed or not on the same population. Moreover, this introspection can be transferred to quite complex dimensions far exceeding the perceived visibility of the eye. This is made possible by the linear optimization technique to grant a feat that requires enough reduction without distortion of reality. Descriptive statistics are generally based on three main approaches: approach to a super-point, clustering approach according to a criterion and finally that which consists of explaining the connection between two or more given phenomena. I II. Mathematical or inferential statistics Statistical inference is initially non-descriptive but rather inductive. Because it consents to estimate an unknown character of a set of observations from a sampling of a sample with well-defined properties. This definition is a means of circumventing the difficulty of accessing very expensive information by an estimate (inference) with the inclusion of a margin of error. The goal is to be able to conclude on the whole with estimators in a judicious and effective way. However, the story of inference begins at the end of the nineteenth century with the work of eminent mathematicians on the likelihood, the test, the intervals of trust, the quality of the estimators. These works are experiencing a breathtaking rise with the arrival of more powerful calculating machines. In general, statistical inference techniques can be grouped according to two approaches: one based on the estimation of the parameters of a statistical population and the other on the assertion of a hypothesis. That is why it is, in my opinion, the only discipline capable of studying both reality and unreality on the principles of scientificity. As a result, it is competitive with other disciplines without distinctions including statistics and physics have allowed the major discovery of the Higgs boson; statistics and mathematics: Shannon's entropy; statistics and biology: ascending hierarchical classification ... etc.
In general terms, Statistics is the science that studies data, resurfaces key information in a set of data (just like a treasure in a vault) and makes it possible to better explain all facts or absurd phenomena. On the other hand, it is an instrument that goes beyond the limit of other sciences (the power of statistics or super science) with random estimation techniques.
Abdi-Basid ADAN, 2018.
https://www.researchgate.net/publication/324978899_The_precepts_of_statistics
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