Variables and constants that appear in a mathematical expression can be defined as parameters , and their variation enables the solution of problems. Thus, a parameter establishes the numerical representation of a large amount of information that derives from the study of a variable. Its calculation is usually performed using an arithmetic formula previously elaborated from data obtained from a population.
Why are parameters important?
When a mathematician approaches the study of a variable, he is faced with an infinity of numbers that are presented in a disordered way. Therefore, it is necessary to work on this information beforehand in order to reduce and organize it and thus be able to work in a simpler and more effective way. Parameter
Although the concentration of initial data in a parameter implies the loss of part of the information, this is compensated by being able to carry out comparisons between samples or allow a characterization of the data.
Main statistical parameters
Within statistics , we can differentiate three large groups of parameters: position, dispersion or shape.
Position measurements make it possible to identify an approximate value that groups most of the data. There are two types of dispersion parameters: those with a central tendency (mean, mode and median) and those with a non-central position (percentiles, deciles and quartiles). Parameter
In turn, information, being necessary to accompany other accessory parameters that give information about the heterogeneity of the data.
Among the most prominent dispersion parameters are: variance, typical deviation, coefficients of variation and range
Finally, the shape parameters indicate the shape that the data histogram presents, being the most common representation: the Gauss curve. It is also worth highlighting the skewness and kurtosis coefficients. Parameter
On the other hand, there are statistical parameters used for a specific purpose, such as the Gini index that serves to measure inequality.