As we have already seen on our website, statistics is a branch of mathematics that studies variability, as well as the process that generates it, based on laws and probability models, we know that it is necessary to use statistics both to investigate and to understand how we are looking today, in addition to its usefulness to understand the findings of any study. However, what basic concepts do we have in descriptive statistics?
To learn more about statistics, let’s focus on descriptive statistics, this part of the discipline deals with the description of experimental data, specifically the collection, organization and analysis of data about certain or a characteristic of certain individuals belonging to a population or universe (1).
- According to Professor Ignacio Cascos from the Carlos III University of Madrid.
- These are some of the basic concepts of descriptive statistics that we must know.
The population is a well-defined group within which a certain characteristic can be observed.
This feature can be finished or infinite. Therefore, the population size is the number of individuals counted and represented by N (1).
If the population is very large, it is very expensive and often even impossible to consider and analyze each individual, so it is common to make a selection called sample.
Every subject in the population is called a subject. These elements do not necessarily have to be people, although this is the most common in psychology.
A sample is a group of individuals of the population that best reflects its characteristics as a whole, if the characteristics reflect the reality it is said that the sample is representative of the population, the sample size is the number of individuals it has, also indicated by N.
A variable (X) is a symbol that represents a characteristic studied within this population. We call data (R) the value, numeric or not, of the variable relative to a specific subject in the sample.
It is important to note that we are talking about descriptive statistics, is that there are several types of variables.
This type of variable has values that correspond to the non-serifiable characteristics of subjects, it cannot be said that one characteristic is better than the other.
Sex is an example of such variables, they are described as qualitative because the differences between categories are only qualitative.
These are variables that can be divided into categories. Unlike a purely qualitative variable, this type of ordinal variable can be categorized.
One can think, for example, of the notes of a test. A person with a higher score was comparatively better than a person who scored lower. They can be sorted in order of magnitude.
The quantitative variable accepts the values of a set of previously set numeric values, this means that we can measure and evolve. Within the quantitative variable, we find two types:
In statistics, we can determine the position of our data from position measures. Here are some:
Central trend measures are typical or representative values of a dataset; in this way, they aim to summarize all the data into one value.
This is a basic concept and also important for descriptive statistics. There are three most commonly used measures of the central trend: fashion (for qualitative variables), median (for categorical variables) and average (for quantitative variables).
There are many other concepts that can be used in descriptive statistics, but these are perhaps the most basic, so, using these concepts, is the statistic responsible for statistically organizing, understanding and calculating the representations of the data to be proposed to the researcher?And by extension to the scientific community?a complete map of what happened in the study.