Types of graphs: the various ways to represent data visually
Translating a somewhat confusing set of data into simple images is quite an art.
All scientific research is based on a set of data that has been properly analyzed and interpreted. properly analyzed and interpreted. To reach a point where we can extract causal or correlation relationships, it is necessary to observe multiple observations in order to falsify and verify the existence of the same relationship in different cases or in the same subject over time. And once these observations have been made, it is necessary to take into account aspects such as the frequency, mean, mode or dispersion of the data obtained.
In order to facilitate 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 visual elements that are easy to interpret: graphs or charts.
Depending on what we want to show, we can use different types of graphs. In this article we will look at different types of graphs that are used in research from the use of statistics.
The graph
To a statistical and mathematical level, we denominated graph to that visual representation from which generally numerical values can be represented and interpreted. generally numerical values. Among the multiple information extractable from the observation of the graph we can find the existence of a relationship between variables and the degree to which it occurs, the frequencies or the proportion of occurrence of certain values.
This visual representation helps to show and understand in a synthesized way the data collected during the research, so that both the researchers carrying out the analysis and others can understand the results and it is easy to use. can understand the results and it is easy to use it as a reference, as information to be taken into account, or as information to be used as a reference.The results can be easily used as a reference, as information to be taken into account or as a point of contrast when carrying out new research and meta-analysis.
Types of graphs
There are many different types of graphs, generally applying one or the other depending on what is to be represented or simply on the author's preferences. The following are some of the best known and most common ones.
1. Bar chart
The best known and most used of all types of graphs is the bar graph or bar chart. In this, the data are 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 the bars.The visual aspect that indicates the data is the length of these bars, their 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 on the abscissae, and the frequencies on the coordinates.
Pie chart or pie chart
In this case the representation of the data is carried out by dividing a circle into as many parts as values of the variable under investigation, each part having a size proportional to its frequency within the total data. a size proportional to its frequency within the total data.. Each sector will represent a value of the variable we are working with.
This type of graph or diagram is usual when showing the proportion of cases within the total, using percentile values (the percentage of each value) to represent it.
3. Histogram
Although at first glance very similar to the bar chart, the histogram is one of the most important and reliable types of graphs at a statistical level. On this occasion, bars are also used to indicate through Cartesian axes the frequency of certain values, but instead of being limited to establishing the frequency of a specific value of the evaluated variable, it reflects an entire interval. Thus, a range of values is observed, which in addition may even 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 to infer the probability. It is generally used for continuous variables, such as time.
4. Line chart
In this type of chart, lines are used to delimit the value of a dependent variable with respect to an independent variable.. 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 usually used to observe the evolution of a variable over time.
A clear example of this type of graphs are frequency polygons. Its operation is practically identical to that of histograms, although using points instead of bars, with the exception that it allows the slope between two such points to be established and the comparison between different variables related to the independent variable or between the results of different experiments with the same variables, such as, for example, the measurements of an investigation with respect to the effects of a treatment, by observing the data of a variable pre-treatment and post-treatment..
8. Scatter plot
The scatter plot or xy plot is a type of graph in which the Cartesian axes are used to represent all the data obtained through observation in the form of points. 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 are related. or two variables of the one being observed if they have some kind of relationship.
The points represented the value reflected in each observation, which at a visual level will show a cloud of points through which we can observe the level of dispersion of the data.
It can be observed whether or not there is a relationship between the variables by means of calculation. This is the procedure usually used, for example, to establish the existence of linear regression lines to determine if there is a relationship between variables and even the type of existing relationship.
9. Box and whisker plots
Box plots are one of the types of graphs that tend to be used to observe the dispersion of the data and how they group their values. It is based on the calculation of 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 graphical representation of the extreme values.
This graph is useful when evaluating intervalsand to observe the level of dispersion of the data from the values of the quartiles and extreme values.
10. Area chart
This type of graph shows, similarly to line graphs, the relationship between dependent and independent variables. Initially a line is drawn joining the points that mark the different values of the measured variable, but also includes everything that is but also includes everything below it: this type of graph allows us to see the accumulation (a given point includes those below it).
Through it, the values of different samples can be measured and compared (e.g., comparing the results obtained by two persons, companies, countries, by two records of the same value....). The different results can be stacked and the differences between the various samples can be easily observed.
11. Pictogram
A pictogram is a graph in which, instead of representing the data using abstract elements such as bars or circles, elements specific to the subject matter are used, elements specific to the subject under investigation are used.. This makes it more visual. However, its operation is similar to that of the bar chart, representing frequencies in the same way as the bar chart.
12. Cartogram
This graph is useful in the field of epidemiology, indicating the zones or geographical areas in which a certain value of a variable appears with greater or lesser frequency. Frequencies or frequency ranges are indicated by the use of color (requiring a legend to be understood) or size.
(Updated at Apr 13 / 2024)