A simple way to remember this is that the value of the dependent variable depends on the value of the independent variable. For example, if you were making a scatter plot that compares people’s age with their height, the independent variable will be the age. The dependent variable will be the person’s height, as that’s the variable that will change and vary based on the person’s age.
If you’re charting age against height, the age of the people you measured would go along the x-axis. If the youngest person you measured was 1 year old, and the oldest person you measure was 20 years old, you’d need 20 points evenly spaced along the line counting from 1 to 20. Use graph paper when drawing a scatter plot to make it easier. Use 1 box on the graph paper for each of the unique results you have in your independent variable. For example, you could draw a line 20 boxes long for a scatter plot comparing age with height of people aged 1 to 20.
For example, a scatter plot comparing age vs. height would have the height on the y-axis. If the shortest person you measured was 1 foot (0. 30 m) tall, and the tallest person was 6 feet (1. 8 m) tall, you could mark 6 points along the y-axis. Alternately, you could mark 12 points so every second point adds 1⁄2 foot (0. 15 m). You could also mark a point for every 1 inch (2. 5 cm) to make a very large scatter plot. If you’re measuring in centimetres and meters, you could mark a point for every 10 centimetres (3. 9 in) of height in the range.
Graph paper will make this much easier, as there are already lines drawn on the scatter plot to help you line everything up. Use a ruler, or even 1 ruler along each axis, to make sure your dots are placed perfectly. If you go to mark a point on the scatter plot but there’s already a point there, you can skip it. Alternately, you could add another dot very close to it, or make that dot slightly bigger. If you’re comparing age and height, you could start with someone who is 13 years old and 5 feet (1. 5 m) tall. Find the number 13 on the x-axis, and then move upwards until your pencil or pen lines up with the number 5 on the y-axis. Make a mark and repeat with every other data point you have.
For a scatter plot comparing age vs. height, you could label the x-axis “Age in Years” and the y-axis “Height in Feet. " The graph could be titled “Age vs. Height. " If you don’t know what to call your scatter plot, labeling it “[X-axis label] vs. [Y-axis label]” is almost always acceptable. Use coloring pencils, different colored pens, or anything else you have to make your scatter plot look more interesting. Make sure that you can still see all of the information you have marked down though!
For example, if you’re comparing temperature with the time of day it is, the hour of the day would be the independent variable, and the temperature would be the dependent variable.
Most spreadsheet and graphing programs will expect the independent variable to be in the left column and the dependent variable to be in the right. If your program is different, you may need to edit the scatter plot slightly once it’s generated. If you’re comparing temperature with the time of day, you could put 7, 8, 9, 10, and so on down the first column to represent the time of day. Then, input the temperature you recorded in the column beside it. So if it was 55 °F (13 °C) at 7am, you could put 7am in one cell, and 55 in the cell beside it.
The scatter plot button has 2 axis with dots scattered in between them, and may be the last button in the “Charts” section.
You can also click on the button made of 9 small boxes that looks like a spreadsheet beside the “Data range” input box. This will let you click and drag over the data you want to use for your scatter plot.
In Excel, you can select the green plus button beside the graph to add more labels and features to the scatter plot. You can also play around in the “Design” and “Format” tabs that appear when you select the graph to change the look of it further. In Google Sheets, you can use the “Chart editor” tab that appears when you insert a chart to edit the look and style of your scatter plot. Use the “Data” tab to edit the data used to make your scatter plot, and use the “Customize” tab to change the way it looks.
