Types of graphs: the various ways to represent data

All research of a scientific nature is supported and based on a set of data properly analyzed and interpreted. To reach a point where we can extract causal or correlational relationships, it is necessary to observe multiple observations. so that it is possible to falsify and verify the existence of the same relationship in different cases or in the same subject through the time. And once these observations have been made, it is necessary to take into account aspects such as the frequency, the average, the mode or the dispersion of the data obtained.

In order to facilitate the understanding and analysis both by the researchers themselves and in order to show the variability of the data and where the conclusions come from to the rest of the world, it is very useful to use easy-to-interpret visual elements: graphs or graphics.

Depending on what we want to show, we can use various types of graphs. In this article We will see different types of graphs that are used in research from the use of statistics.

• Related article: "The 15 types of research (and characteristics)"

The graphic

At a statistical and mathematical level, called graphics to that visual representation from which they can be represented and interpreted Usually numeric values. Among the multiple extractable information from the observation of the graph we can find the existence of relationship between variables and the degree to which it occurs, the frequencies or the proportion of appearance of certain values.

This visual representation serves as support when it comes to showing and understanding the data in a synthesized way. collected during the investigation, so that both the researchers carrying out the analysis and the others can understand the results and is easy to use as a reference, as information to take into account or as a point of contrast before carrying out new investigations and meta-analyses.

• You may be interested in: "The 5 most common study methods in Psychology"

Types of graphs

There are very different types of graphics, generally applying one or the other depending on what is intended to be represented or simply on the preferences of the author. Here are some of the best known and most common.

1. Bar graphic

The best known and used of all types of charts is the bar graph or chart. In it, the data is presented in the form of bars contained in two Cartesian axes (coordinate and abscissa) that indicate the different values. The visual aspect that indicates the data is the length of said bars, its thickness not being important.

It is generally used to represent the frequency of different conditions or discrete variables (for example, the frequency of the different colors of the iris in a given sample, which can only be specific values). Only one variable is observed in the abscissa, and the frequencies in the coordinates.

• You may be interested in: "Color psychology: meaning and curiosities of colors"

2. Pie or sector chart

The also very common graph in the form of "cheese", in this case the representation of the data is carried out carried out by dividing a circle into as many parts as there are values ​​of the investigated variable and having each part a size proportional to its frequency within the total data. Each sector will represent a value of the variable with which we work.

This type of graph or diagram is common when the proportion of cases within the total is being shown, using percentage values ​​to represent it (the percentage of each value).

3. histogram

Although at first glance very similar to the bar graph, the histogram is one of the types of graph that is more important and reliable at a statistical level. On this occasion, bars are also used to indicate through Cartesian axes the frequency of certain values, but instead of limiting itself to establishing the frequency of a specific value of the evaluated variable, it reflects a whole interval. Thus, a range of values ​​is observed, which also could come to reflect intervals of different lengths.

This allows us to observe not only the frequency but also the dispersion of a continuum of values, which in turn can help to infer probability. It is generally used before continuous variables, such as time.

4. line chart

In this type of graph, lines are used to delimit the value of a dependent variable with respect to an independent one. It can also be used to compare the values ​​of the same variable or of different investigations using the same graph (using different lines). It is usual that it is used to observe the evolution of a variable over time.

A clear example of this type of graphics are frequency polygons. Its operation is practically identical to that of histograms, although using points instead of bars, with the exception that it allows establish the slope between two of these points and the comparison between different variables related to the independent or between the results of different experiments with the same variables, such as the measures of an investigation regarding the effects of a treatment, observing the data of a variable pretreatment and posttreatment.

8. Scatter plot

The scatter graph or xy graph is a type of graph in which all the data obtained by observation are represented in the form of points by means of the Cartesian axes. The x and y axes each show the values ​​of a dependent variable and an independent variable. or two variables of the one being observed if they present some type of relationship.

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

Whether or not there is a relationship between the variables can be observed by calculus. It is the procedure that is usually used, for example, to establish the existence of lines of linear regression that allows determining if there is a relationship between variables and even the type of relationship existing.

9. Box and whisker plot

Boxplots are one of the types of graphs that tend to be used in order to observe the dispersion of the data and how they group their values. It starts from the calculation of the quartiles, which are the values ​​that allow the data to be divided into four equal parts. Thus, we can find a total of three quartiles (the second of which would correspond to the median of the data) that will configure the "box" in question. The so-called whiskers would be the graphic representation of the extreme values.

This graph It is useful when evaluating intervals, as well as observing 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 the dependent and independent variable is observed, in a similar way to what happens with line graphs. Initially a line is made that joins the points that mark the different values ​​of the variable measure, but everything below it is also included: this type of graph allows us to see the accumulation (a given point includes those below it).

Through 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 worth….). The different results can be stacked, easily observing the differences between the various samples.

11. pictogram

A pictogram is understood to be a graph in which, instead of representing the data from abstract elements such as bars or circles, Elements of the topic being investigated are used. In 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 geographical zones or areas in which a certain value of a variable appears with greater or lesser frequency. Frequencies or frequency ranges are indicated by use of color (a legend is required to be understood) or size.