**All scientific research is supported and based on a set of data** duly analyzed and interpreted. To get to a point where we can extract causal or correlational relationships, it is necessary to observe multiple observations so that the existence of the same relationship can be falsified and verified in different cases or in the same subject over time. . And once these observations are made, aspects such as the frequency, the average, the mode or the dispersion of the data obtained must be taken into account.

In order to facilitate understanding and analysis both by the researchers themselves and to show the variability of the data and where the conclusions are coming from in the rest of the world, it is very useful to use visuals that are easy to understand. interpret .: Graphics or graphs.

Depending on what we want to show, we can use different types of graphics. In this article **we will see different types of graphics** which are used in research from the use of statistics.

Table of Contents

## the graphic

At the statistical and mathematical level, called graph one **this visual representation from which they can be represented and interpreted** usually numeric values. Among the many information that can be extracted from the observation of the graph, we can find the existence of a relation between the variables and the degree to which it occurs, the frequencies or the proportion of occurrence of certain values.

This visual representation supports the synthesis and understanding of the data obtained during the research, so that the researchers performing the analysis and others can **they can understand the results and it is easy to use it as a reference**, As information to be taken into account or as a point of contrast before carrying out new research and meta-analyzes.

## Types of charts

There are many different types of graphics, usually applying one or the other depending on what you want to depict or just the author’s preferences. Here are some of the best known and most common.

### 1. Bar graph

The best known and most widely used of all types of charts is the bar chart. In this, the data is presented in the form of bars contained in two Cartesian axes (coordinates and abscissa) which indicate the different values. **The visual aspect that the data tells us is the length of these bars**, And its thickness does not matter.

It is generally used to represent the frequency of different conditions or discrete variables (e.g. the frequency of different iris colors in a given sample, which can only be specific values). A single variable is observed on the x-coordinates, and the frequencies on the coordinates.

### 2. Pie or pie chart

The graph also very common in the form of “cheese”, in this case the representation of the data is carried out by dividing a circle into as many parts as the values of the studied variable and having each part **a size proportional to its frequency in the total data**. Each sector represented a value of the variable it is working with.

This type of graph or chart is common when the proportion of cases in the total is displayed, using to represent values as a percentage (the percentage of each value).

### 3. Histogram

Although at first glance very similar to the bar graph, the histogram is one of the most important and reliable types of graphs statistically. On this occasion, bars are also used to indicate by Cartesian axes the frequency of certain values, but instead of simply establishing the frequency of a specific value of the evaluated variable, they reflect an entire range. We therefore observe a range of values which in addition **they might come to reflect intervals of different lengths**.

This makes it possible to observe not only the frequency but also the dispersion of a continuum of values, which in turn can help infer the probability. It is generally used when dealing with continuous variables, such as time.

### 4. Line graph

In this type of chart, lines are used to **delimit the value of a dependent variable from another independent**. It can also be used to compare values of the same variable or of different investigations using the same graph (using different rows). It is generally used to observe the evolution of a variable over time.

A clear example of this type of graph is frequency polygons. Its operation is practically identical to that of histograms although using points instead of bars, except that it allows to establish the slope between two of these points and the comparison between different variables linked to the independent or between the results of different experiments with the same variables, such as the measures of a survey versus the effect of a treatment, **observation of the data of a preprocessing and postprocessing variable**.

### 8. Point cloud

Scatter plot or xy graph is a type of graph in which, by means of Cartesian axes, all the data obtained by means of observation is represented as points. **The x and y axes each display the values of a dependent variable and an independent variable** or two variables which it is observed if they exhibit some type of relationship.

The points represented the value reflected in each observation, which at the visual level will show a scatter plot through which we can observe the level of dispersion of the data.

We can observe whether or not there is a relationship between the variables by calculation. It is the procedure usually used, for example, to establish the existence of lines of linear regression which makes it possible to determine if there is a relation between the variables and even the type of relation which exists.

### 9. Box and mustache graphic

Cash charts are one of the types of charts that tend to be used to observe the dispersion of data and how they group their values. It is based on the calculation of quartiles, which are the values that **they allow to divide the data into four equal parts**. Thus, we can find a total of three quartiles (the second of which would correspond to the mean of the data) which will constitute the “box” in question. The so-called mustaches are said to be the graphic representation of extreme values.

this graphic **it is useful when evaluating intervals**, As well as to observe the level of dispersion of the data from the values of the quartiles and the extreme values.

### 10. Area chart

In this type of graph, the relationship between dependent and independent variables is observed, like what happens with line graphs. initially **a line is made which joins the points which mark the different values of the variable** measure, but also includes all of the following: this type of chart allows us to see accumulation (some point includes those below).

Thanks to it, you can measure and compare the values of different samples (for example, compare the results obtained by two people, companies, countries, by two records of the same value ….). The different results can be stacked, easily observing the differences between the different samples.

### 11. Pictogram

A pictogram is a graphic in which, instead of representing data from abstract elements such as bars or circles, **elements specific to the subject studied are used**. This way it becomes more visual. However, its operation is similar to that of the bar graph, representing frequencies in the same way.

### 12. Cartogram

This graph is useful in the field of epidemiology, indicating the areas or geographic areas in which a certain value of a variable appears more or less frequently. Frequencies or frequency ranges are indicated by the use of color (requiring a legend to understand it) or size.

#### Bibliographical references:

- Martinez-Gonzalez, MA; Faulin, FJ and Sánchez, A. (2006). Friendly biostatistics, 2nd ed. Diaz de Santos, Madrid.