Login

A Simple Scatterplot using SPSS Statistics

Introduction

A simple scatterplot can be used to (a) determine whether a relationship is linear, (b) detect outliers and (c) graphically present a relationship between two continuous variables. For example, determining whether a relationship is linear (or not) is an important assumption if you are analysing your data using Pearson's product-moment correlation, Spearman's rank-order correlation, simple linear regression, multiple regression, amongst other statistical tests.

Note: If you are analysing your data using an ANCOVA (analysis of covariance) or two-way ANOVA, for example, you will need to consider a grouped scatterplot instead (N.B., if you need help creating a grouped scatterplot using SPSS Statistics, we show you how in our enhanced content).

For example, a simple scatterplot could be used to determine if there is a linear relationship between lawyers' salaries and the number of years they have practiced law (i.e., your dependent variable would be "salary" and your independent variable would be "years practicing law"). A simple scatterplot could also be used to determine if there is a linear relationship between the distance women can run in 30 minutes and their VO2max, which is a measure of fitness (i.e., your dependent variable would be "distance run" and your independent variable would be "VO2max").

The purpose of this guide is to show you how to create a simple scatterplot using SPSS Statistics. First, we introduce the example we have used in this guide. Next, we show how to use the Chart Builder in SPSS Statistics to create a simple scatterplot based on whether you have SPSS Statistics versions 27 or 28 (or the subscription version of SPSS Statistics), versions 25 or 26, or version 24 or an earlier version of SPSS Statistics. If you are unsure which version of SPSS Statistics you are using, see our guide: Identifying your version of SPSS Statistics.

SPSS Statistics

Example

This guide will use the example from the linear regression guide, where researchers wanted to determine if there was a linear relationship between cholesterol concentration (a type of fat in the blood) and the time spent watching TV in otherwise healthy 45 to 65 year old men (an at-risk category of people for heart disease). They believed that there would be a positive relationship: the more time people spent watching TV, the greater their cholesterol concentration.

Daily time spent watching TV was recorded in the variable time_tv and cholesterol concentration recorded in the variable cholesterol. Therefore, to determine whether a linear relationship exists between the two continuous variables, which is one of the assumptions that must be met when running a linear regression, the researchers generated a simple scatterplot by plotting the dependent variable, cholesterol, against the independent variable, time_tv.

Testimonials
TAKE THE TOUR


SPSS Statistics

SPSS Statistics procedure for versions 27 and 28
(and the subscription version of SPSS Statistics)

The eight steps that follow show you how to create a simple scatterplot in SPSS Statistics versions 27 and 28 (and the subscription version of SPSS Statistics) using the example above.

  1. Click Graphs > Chart Builder... on the main menu, as shown below:
    'Chart Builder' menu for a simple scatterplot in SPSS Statistics

    Published with written permission from SPSS Statistics, IBM Corporation.


    You will be presented with the Chart Builder dialogue box, as shown below:
    'Chart Builder' dialogue box for a simple scatterplot in SPSS Statistics

    Published with written permission from SPSS Statistics, IBM Corporation.

  2. Select "Scatter/Dot" from the Choose from: box in the bottom-left-hand corner of the Chart Builder dialogue box, as shown below:
    The 'Scatter/Dot' option is highlighted

    Published with written permission from SPSS Statistics, IBM Corporation.

  3. Selecting "Scatter/Dot" will present seven different scatter/dot options in the lower-middle section of the Chart Builder dialogue box (as shown above and below). Drag-and-drop the top-left-hand option (you will see it labelled as "Simple Scatter" if you hover your mouse over the box) into the main chart preview pane, as shown below:
    7 different scatterplot options are presented. The 'Simple Scatter' option is dragged into the 'Chart Preview' box at the top

    Published with written permission from SPSS Statistics, IBM Corporation.

  4. You will be presented with the screen below, which shows a simple scatterplot in the main chart preview pane with boxes for the y-axis ("Y-Axis?") and x-axis ("X-Axis?") for you to populate with the appropriate variables.
    The 'Chart Preview' pane changes, simply highlighting you are going to create a simple scatterplot

    Published with written permission from SPSS Statistics, IBM Corporation.

    Note: You can ignore the "Set size?" and "Filter?" boxes.

  5. Drag-and-drop the independent variable, time_tv, from the Variables: box into the "X-Axis?" box in the main chart preview screen and do the same for the dependent variable, cholesterol, but into the "Y-Axis?" box. You should end up with a screen like the one below:
    The 'Chart Preview' changes to reflect the variables you have entered into the a-axis and y-axis of your simple scatterplot

    Published with written permission from SPSS Statistics, IBM Corporation.

    Note: The chart preview pane does not accurately plot the variable data that you have dragged into its preview pane, even though it might appear that it does due to the simple scatterplot dots changing when you add your variables. Therefore, do not get confused and think that you have done something wrong. You will only see your true data when you actually generate the simple scatterplot.

  6. Click on "Y-Axis1 (Point1)" in the element properties dialogue box and you will be presented with the following screen:
    The 'Element Properties' dialogue box provides further options to edit your simple scatterplot

    Published with written permission from SPSS Statistics, IBM Corporation.

    Note: You can use this dialogue box to change the axis label (using the Axis Label: box) and/or change scale attributes using the options in the –Scale Range– area.

  7. Uncheck the Minimum option in the –Scale Range– area so that the Custom value is highlighted and has a value of 0 (zero), as shown below:
    You can now make changes to the y-axis of your simple scatterplot

    Published with written permission from SPSS Statistics, IBM Corporation.

    Note: The procedure above (steps 6 and 7) are intended to make the y-axis show a suitable range of values for cholesterol concentration. These values might be different for your variables, so you should adjust them as you see fit. If you are not sure at first what these values should be, don't change these values; see what the simple scatterplot looks like, and then re-run the simple scatterplot with new axes values.

  8. Click on the OK button in the Chart Builder dialogue box to generate the simple scatterplot below:
    Simple scatterplot showing 'cholesterol' by 'time_tv'

    Published with written permission from SPSS Statistics, IBM Corporation.

    Note: If we had not change the scale of the y-axis in steps 6 and 7 above, the simple scatterplot would have looked as follows:
    Simple scatterplot showing 'cholesterol' by 'time_tv' with scale changed on y-axis

Note: If the type of simple scatterplot that you want to create is different from the example above or there are specific options you want to include in your simple scatterplot that we have not covered, please contact us. We will try to add a section to the guide that deals with the type of simple scatterplot you want to create.

If you would like to add a line of best fit, or confidence and prediction intervals, which are useful when carrying out a linear regression analysis, we show you how to do this in our enhanced simple scatterplot guide. You can access this enhanced guide, as well as all other enhanced guides in our site, by subscribing to Laerd Statistics.

Join the 10,000s of students, academics and professionals who rely on Laerd Statistics.TAKE THE TOUR
next »