Charts

In charts, data is represented graphically, therefore they are used in statistics mainly to get an overview of the collected data and to prepare information in an easily understandable way.

The most frequently used charts in statistics are:

• Bar chart
• Histogram
• Scatterplot
• box plot

Histogram

A histogram is a graphical representation of the frequency distribution of a metric variable. To display a distribution of data in a histogram, the data must first be divided into classes, also called bins. These classes or bins are then represented by rectangles that lie directly next to each other.

This is also the main difference to bar charts, in a bar chart the data are already grouped from the beginning and do not have to be divided into groups as in a histogram. This becomes graphically clear, as in a bar chart there is a distance between the bars.

Accordingly, histograms are used for metric variables such as salary or age, and bar charts for ordinal or nominal variables such as gender or school grade.

Example Histogram

The creation of graphical representations such as the histogram will now be explained using an example. The aim of the example is to graphically represent the frequency distribution of the results of a statistical test. The starting point is the table below with the respective scores of the 12 students.

This is how it works with DATAtab: Simply copy the above table into the Statistics Calculator, click on Descriptive Statistics and finally select the variable "Score".

You will then see the following graph in DATAtab, which allows you to visualize the results of the statistics exams of 12 students.

Student	Score
1	28
2	29
3	35
4	37
5	32
6	26
7	37
8	39
9	22
10	29
11	33
12	34

Scatter Plots

Scatter plots are used in statistics to visualize correlations in data. In a scatterplot always two variables can be plotted, this is done by representing each pair of values of a case as a point in a coordinate system. If, for example, 10 persons are asked for their weight and height, the scatterplot shows 10 points.

With the help of the scatterplot you get a first indication of the correlation between the two visualized variables. If high values of one variable are associated with high values of the other variable, there is a positive correlation. If high values of one variable are associated with low values of the other variable, there is a negative correlation. If the points are randomly distributed, there is no correlation.

Furthermore, there can also be a non-linear relation, in this case there is a pattern in the distribution of the points, but no straight line can be drawn through the points.

Create charts online

Charts are a valuable tool for visually presenting information. On Datatab you can create your own charts online and free of charge.

With DATAtab-charts you can easily create your charts online. To create a chart, simply select the chart type you want to create and copy your data to the table above. Which chart you create depends on what information you want to convey and the scale level of your data. DATAtab charts are constantly being expanded, currently the following charts are available:

• Barchart
• Boxplot
• Histogram
• Scatter Plot

Create charts

Charts allow you to present complex information clearly and offer the reader the advantage that he can quickly get an overview of your results. In statistics, it is advisable to first examine the data with the help of the charts created, this already gives an indication of whether there are differences in the individual groups, for example. Afterwards, the visual results can be used to test hypotheses.