Introduction

A simple scatterplot is one of the most useful charts in data analysis, as it allows the researcher to explore the relationship between two continuous variables. With its help, one can examine whether the relationship between the variables is linear, identify potential outliers, and visually depict the correlation of the data. For example, if we are analyzing data intended for testing with Pearson’s product–moment correlation, Spearman’s rank correlation, or even regression analysis, visually confirming linearity through a scatterplot is fundamental.

Importance of the Scatterplot

The usefulness of such a chart is not limited to checking linearity. In fact, through a simple scatterplot we can gain an initial understanding of the nature of the relationship between two variables. This includes whether the relationship is positive or negative, whether it follows a curve, or is completely random. Moreover, scatterplots are invaluable for identifying outliers that may significantly influence the results of a statistical analysis. For instance, a very high or very low score on one variable can distort the correlation coefficient, making early detection essential.

Example of Use

A typical example could involve analyzing the relationship between lawyers’ salaries and their years of professional experience. In this case, the dependent variable is salary, while the independent variable is years of practicing law. By using a simple scatterplot, we can observe whether a positive linear relationship exists—that is, whether salaries increase as years of experience increase. Another example involves the relationship between the distance women can run within 30 minutes and their VO2max, which is a measure of fitness. Here, the dependent variable is running distance, while the independent variable is VO2max. The scatterplot will show us whether women with higher VO2max can indeed cover longer distances.

Creating a Scatterplot in SPSS

To create a simple scatterplot in SPSS, we use the Chart Builder tool. This procedure allows the user to place the dependent variable on the vertical axis (Y) and the independent variable on the horizontal axis (X). From there, SPSS generates the chart, which can be customized by adding titles, labels, and regression lines. It is important to note that starting with SPSS version 25, some elements of the Chart Builder have changed, so the procedure is slightly different compared to earlier versions.

SPSS Version 25 and Later

In the newer versions of SPSS, including the subscription edition, creating a scatterplot is particularly user-friendly. We select Graphs > Chart Builder, then choose Scatter/Dot and place the variables on the corresponding axes. The software provides a preview, so we know exactly what the result will look like before the final chart is produced.

SPSS Version 24 and Earlier

In older versions, the procedure is similar but with fewer preview and customization options. Nevertheless, the outcome is the same: a chart that clearly shows the potential relationship between the two variables.

Conclusions

The simple scatterplot is a fundamental tool in statistical analysis. It is used to investigate linearity, identify outliers, and provide an immediate visual representation of the relationship between two continuous variables. In SPSS, the process of creating it is straightforward and can be adapted depending on the version of the software the researcher is using. Whether it concerns the analysis of salaries and experience or fitness data, the scatterplot is the first graphical representation that will help us better understand the data and proceed more accurately to more advanced statistical tests.